CN113952730A

CN113952730A - Data processing method and device, electronic equipment, storage medium and computer product

Info

Publication number: CN113952730A
Application number: CN202111240966.9A
Authority: CN
Inventors: 李旭冬; 袁明凯; 王谊; 罗章龙; 严明
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2021-10-25
Filing date: 2021-10-25
Publication date: 2022-01-21
Anticipated expiration: 2041-10-25
Also published as: CN113952730B

Abstract

The embodiment of the application discloses a data processing method and device, electronic equipment, a storage medium and a computer product, and relates to the fields of games, cloud technologies and artificial intelligence. The method comprises the following steps: respectively executing at least one optimization operation aiming at each initial lineup in the initial lineup set, and determining a target lineup based on the optimized initial lineup set, wherein the optimization operation comprises the following steps: determining the strength of the initial lineup; determining array capacity elements to be replaced in the initial array capacity; determining new array capacity elements from the candidate array capacity elements based on the linkage coefficient between the array capacity elements reserved in the initial array capacity and the candidate array capacity elements, and replacing the array capacity elements to be replaced by the new array capacity elements; determining the strength of the replaced lineup; and taking the array capacity with larger array capacity strength in the initial array capacity and the replaced array capacity as a new initial array capacity corresponding to the initial array capacity. Based on the scheme provided by the embodiment of the application, the target formation with higher fighting capacity can be automatically generated.

Description

Data processing method and device, electronic equipment, storage medium and computer product

Technical Field

The present application relates to the field of artificial intelligence, cloud technology, and multimedia technology, and in particular, to a data processing method, apparatus, electronic device, storage medium, and computer product.

Background

In recent years, with the development of science and technology and the improvement of living standard of people, games have been popularized greatly. In many games, such as Simulation games (SLG), a player can match his/her own lineup with a virtual character provided by the Game and virtual skills available to the virtual character, and then match up with the lineup of another player using the lineup. In order to assist the player to match the formation with stronger fighting capacity, the game can provide a plurality of high ladder formation with stronger fighting capacity as the reference for matching the formation.

In the prior art, a plurality of avatars are constructed by game staff (such as game planners and game developers) according to the cognition of the game staff on the game, and the avatars are used as avatars recommended to players. However, the game developer may not have all the content of the swordsman, and is limited by the limited understanding degree of the game developer on the game, the fighting power of the formation constructed by the game developer may not be strong, and if the player uses the formation as the formation matching reference, it is often not favorable for the player to match the formation with high fighting power, and recommending the formation to the player may cause dissatisfaction of the player, which may reduce the game experience of the player, resulting in the loss of the player. In addition, the mode of determining the formation of the elevator has the disadvantages of high labor cost and low efficiency.

Disclosure of Invention

The application aims to provide a data processing method, a data processing device, electronic equipment, a storage medium and a computer product, wherein the data processing method can automatically generate a target formation with high fighting capacity. In order to achieve the purpose, the technical scheme provided by the embodiment of the application is as follows:

in one aspect, the present application provides a data processing method, including:

acquiring an initial lineup set, wherein the initial lineup set comprises a plurality of initial lineups, and each initial lineup comprises a plurality of lineup elements;

executing at least one optimization operation aiming at each initial lineup in the initial lineup set, determining a target lineup based on the optimized initial lineup set, wherein the optimization operation comprises the following steps of:

determining a first array strength of the initial array;

determining array capacity elements to be replaced in the initial array capacity;

determining new array capacity elements corresponding to the array capacity elements to be replaced from the candidate array capacity elements based on the linkage coefficient between the array capacity elements reserved in the initial array capacity and the candidate array capacity elements; the continuous carrying coefficients among the array elements represent the fighting capacity which can be additionally generated by the combination among the array elements;

replacing the array capacity element to be replaced by adopting a new array capacity element, and determining a second array capacity strength of the replaced array capacity;

and determining the lineup corresponding to the larger lineup intensity in the first lineup intensity and the second lineup intensity as a new initial lineup corresponding to the initial lineup in the initial lineup set.

In another aspect, an embodiment of the present application provides a data processing apparatus, including:

the initial lineup acquiring module is used for acquiring an initial lineup set, wherein the initial lineup set comprises a plurality of initial lineups, and each initial lineup comprises a plurality of lineup elements;

the target lineup determining module is used for executing at least one optimization operation aiming at each initial lineup in the initial lineup set, determining the target lineup based on the optimized initial lineup set, and for one initial lineup, the optimization operation comprises the following steps:

determining a first array strength of the initial array;

Optionally, one initial lineup includes at least two types of lineup elements, and each candidate lineup element corresponding to one lineup element to be replaced is a lineup element belonging to the same type as the lineup element to be replaced; when determining a new lineup element corresponding to the lineup element to be replaced from each candidate lineup element, the target lineup determination module may be configured to:

for each candidate lineup element, determining a first importance of the candidate lineup element based on at least one of a continuous coefficient between a first lineup element of the initial lineup and the candidate lineup element or a continuous coefficient between a second lineup element of the initial lineup and the candidate lineup element, wherein the first importance represents an importance degree of the candidate lineup element in the replaced lineup when the candidate lineup element is used as a new lineup element;

the first array element is an array element in the reserved array elements, which belongs to the same type as the candidate array element, and the second array element is an associated array element of the array element to be replaced, except the first array element, in the reserved array elements;

and determining new formation elements corresponding to the formation elements to be replaced from the candidate formation elements based on the corresponding importance of the candidate formation elements.

Optionally, the at least two types of lineup elements include two types of lineup elements, namely a virtual character and a virtual skill; if the lineup element to be replaced is a virtual character, the related lineup element of the virtual character comprises virtual skills of the virtual character; if the lineup element to be replaced is a virtual skill, the related lineup element of the virtual skill comprises at least one of a target virtual character with the virtual skill or other virtual skills, except the virtual skill, of the target virtual character.

Optionally, when determining the lineup element to be replaced in the initial lineup, the target lineup determining module may be configured to:

for each array element in the initial array, determining a second importance of the array element based on a linkage coefficient between the array element and other array elements in the initial array, wherein the second importance represents an importance degree of the array element in the initial array;

and determining the lineup elements to be replaced from the lineup elements of the initial lineup based on the second importance of the lineup elements in the initial lineup.

Optionally, the plurality of lineup elements include at least two types of lineup elements, for an initial lineup, each time of the optimization operation takes one type of lineup element in the initial lineup as a lineup element to be replaced, and each type of lineup element in the initial lineup corresponds to at least one time of the optimization operation.

Optionally, the lineup elements in the initial lineup and the candidate lineup elements are lineup elements in the target game application; the carry-on coefficient between the formation elements in the target game application is determined by the carry-on relationship determination module by performing the following operations:

acquiring application configuration information of the target game application, wherein the application configuration information comprises configuration information of each formation element in the target game application;

obtaining attribute information of each lineup element based on configuration information of each lineup element

And determining the linkage coefficient among the array elements according to the matching degree among the attribute information of the array elements.

Optionally, one lineup element is a virtual character or a virtual skill; for the virtual role, the attribute information of the lineup element comprises at least one item of lineup, role type or trip of the virtual role; for the virtual skill, the attribute information of the lineup element includes at least one of a skill type, a skill effect, or a skill enhancement condition of the virtual skill.

Optionally, the portable relationship determining module may be configured to:

for two virtual characters, determining a linkage coefficient between the two virtual characters according to at least one of the matching degree between the marketing of the two virtual characters or the matching degree between the detention of the two virtual characters;

for the two virtual skills, determining a linkage coefficient between the two virtual skills according to the matching degree between the skill effect and the skill enhancement condition of the two virtual skills;

for a virtual character and a virtual skill, determining a carry-on coefficient between the virtual character and the virtual skill according to the matching degree between the character type of the virtual character and the skill type of the virtual skill.

Optionally, the apparatus further includes a reference lineup obtaining module, where the module is configured to: acquiring a reference lineup set, wherein the reference lineup set comprises a plurality of reference lineups;

the target lineup determination module, when determining the first lineup strength of the initial lineup, may be configured to:

the initial lineup and each reference lineup in the reference lineup set are combated; and determining a first array capacity strength of the initial array capacity based on the fighting results of the initial array capacity corresponding to the reference array capacities.

In another aspect, an embodiment of the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory, where the processor executes the computer program to implement the steps of the method provided by the embodiment of the present application.

On the other hand, the embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the computer program implements the steps of the method provided by the embodiment of the present application.

In yet another aspect, the present application further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the method provided by the present application.

The technical scheme provided by the embodiment of the application has the following beneficial effects:

the data processing method provided by the embodiment of the application can guide optimization of the initial lineup based on the linkage coefficient between lineup elements, namely, the lineup elements in the initial lineup are replaced, and whether the lineup before replacement is replaced by the lineup after replacement is determined based on the strength of the lineup before replacement and the strength of the lineup after replacement, so that optimization of the initial lineup in the initial lineup set is realized. The scheme realizes automatic optimization of the array capacity by utilizing the continuous carrying coefficients among the array capacity elements, so that the fighting capacity of each array capacity in the initial array capacity set can be continuously improved. Based on the method, the target formation with stronger fighting capacity can be obtained more quickly and accurately. In addition, the method can be free from manual intervention, the labor cost consumed by the method can be greatly reduced, the generation efficiency of the target array capacity is improved, and the actual application requirements are better met.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments of the present application will be briefly described below.

Fig. 1 is a schematic flowchart of a data processing method according to an embodiment of the present application;

fig. 2 is a scene diagram of an application scenario to which the embodiment of the present application is applied;

fig. 3 is a schematic flowchart of a data processing method according to an embodiment of the present application;

fig. 4 is a schematic flowchart of a process for obtaining attribute information of a lineup element according to an embodiment of the present disclosure;

fig. 5 is a schematic flowchart of determining a linkage coefficient between lattice content elements according to an embodiment of the present disclosure;

fig. 6 is a schematic flowchart of optimizing an array capacity according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device to which the embodiment of the present disclosure is applied.

Detailed Description

Embodiments of the present application are described below in conjunction with the drawings in the present application. It should be understood that the embodiments set forth below in connection with the drawings are exemplary descriptions for explaining technical solutions of the embodiments of the present application, and do not limit the technical solutions of the embodiments of the present application.

As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the terms "comprises" and/or "comprising," when used in this specification in connection with embodiments of the present application, specify the presence of stated features, information, data, steps, operations, elements, and/or components, but do not preclude the presence or addition of other features, information, data, steps, operations, elements, components, and/or groups thereof, as embodied in the art. The term "and/or" as used herein indicates at least one of the items defined by the term, e.g., "a and/or B" indicates either an implementation as "a", or an implementation as "a and B".

The method is used for solving the technical problems that the formation generation efficiency is low, the fighting capacity of the generated formation cannot be guaranteed and the like in the existing formation generation mode, and the data processing method is provided.

Optionally, the data processing according to the embodiment of the present application may be implemented based on Cloud technology (Cloud technology), for example, the steps of constructing the initial lineup set and the reference lineup set, determining the carry coefficients between lineup elements, and the like may be implemented by using Cloud technology. The cloud technology is a hosting technology for unifying series resources such as hardware, software, network and the like in a wide area network or a local area network to realize the calculation, storage, processing and sharing of data. The cloud technology is based on the general names of network technology, information technology, integration technology, management platform technology, application technology and the like applied in the cloud computing business model, can form a resource pool, is used as required, and is flexible and convenient. Cloud computing technology will become an important support. Cloud computing refers to a delivery and use mode of an IT infrastructure, and refers to acquiring required resources in an on-demand and easily-extensible manner through a network; the generalized cloud computing refers to a delivery and use mode of a service, and refers to obtaining a required service in an on-demand and easily-extensible manner through a network. Such services may be IT and software, internet related, or other services. With the development of diversification of internet, real-time data stream and connecting equipment and the promotion of demands of search service, social network, mobile commerce, open collaboration and the like, cloud computing is rapidly developed. Different from the prior parallel distributed computing, the generation of cloud computing can promote the revolutionary change of the whole internet mode and the enterprise management mode in concept.

Optionally, the data processing method provided in the embodiment of the present application may also be implemented based on an Artificial Intelligence (AI) technology. For example, the determination of the strength of the formation can be predicted by a trained neural network model (i.e., a prediction model of the strength of the formation). AI is a theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use the knowledge to obtain the best results. As artificial intelligence technology has been researched and developed in a wide variety of fields, it is believed that with the development of technology, artificial intelligence technology will be applied in more fields and will play an increasingly important role.

For better explanation and understanding of the solutions provided in the embodiments of the present application, some relevant technical terms referred to in the embodiments of the present application will be first described:

SLG: the simulation game is a strategic simulation game having a lineup of hero (virtual character in the game) and skill (virtual skill in hero in the game).

Formation capacity: a lineup contains multiple heros, each carrying multiple skills.

The excellent leveling rate: after one array capacity is in match with other array capacities, the number of the winning plays and the number of the peaches of the array capacity are counted, and the ratio of the sum of the number of the winning plays and the number of the peaches of the array capacity to the total number of the matches is used as the optimal average rate.

And (3) formation of the elevator: the array comprises a plurality of array volumes, such as 100 array volumes, each array volume in the ladder array volume has a high optimal rate, and the repeatability of hero among different array volumes is low.

A linked gene: each hero and skill acts as an independent gene, and is called a carried gene if there is an enhanced relationship between hero and hero, skill and skill, hero and skill.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 1 shows a flowchart of a data processing method provided in this embodiment of the present application, where the method may be executed by any electronic device, for example, a terminal device, and the terminal device may determine a plurality of target lineups (which may also be referred to as ladder lineups) based on an initial lineup set by executing the method. The terminal equipment can run an operation management client of the target game application, the operation management client faces to developers or operation managers of the target game application, and the operation of generating the target formation suitable for the target game application can be triggered through the operation management client. Optionally, the method may also be executed by a server, where the server may be an operation management server (also referred to as an operation server) of the target game application, and the server may generate a target formation that may be recommended to the user and has a strong fighting capacity by executing the data generation method provided in the embodiment of the present application.

The terminal equipment comprises a user terminal, wherein the user terminal comprises but is not limited to a mobile phone, a computer, intelligent voice interaction equipment, intelligent household appliances, a vehicle-mounted terminal, wearable electronic equipment, AR/VR equipment and the like.

As shown in fig. 1, the data processing method provided in the embodiment of the present application may include the following step S110 and step S120, and optionally, the method may be executed by a terminal device or a server, where the server may be a physical server, a cloud server, or a server cluster.

Step S110: and acquiring an initial lineup set, wherein the initial lineup set comprises a plurality of initial lineups, and each initial lineup comprises a plurality of lineup elements.

Wherein, the formation elements form the elements required by the game formation. The plurality of lineup elements in a lineup may include one or more types of lineup elements. In practical applications, the requirements of the components of the game lineup (i.e. lineup matching requirements) may be different for different game applications, for example, if the game application is configured with the definition conditions of the game lineup, each initial lineup should be a lineup meeting the requirements. For example, the lineup matching requirements for a game application are: each lineup includes three avatars, each avatar being configurable with two virtual skills. A plurality of initial lineups satisfying the lineup matching requirement can be generated according to the lineup matching requirement.

Optionally, a lineup may contain a plurality of different types of lineup elements, for example, most game lineups may generally include at least two types of lineup elements, namely, a virtual character (also referred to as hero) and a virtual skill possessed by the virtual character.

The number of the initial lineups in the initial lineup set can be configured according to actual requirements, for example, the number of the lineups to be recommended to game players can be determined, that is, the number of the lineups of the skateboarding lineup. The number of initial lineups may be no less than the number of lineups desired to be recommended to the game player.

The embodiment of the present application is not limited to the manner of acquiring multiple initial lineups in the initial lineup set. For example, the initial lineup may be generated by randomly selecting a plurality of lineup elements from all lineup elements of the target application game, or may be generated based on a genetic algorithm, for example, may be a lineup obtained by performing multiple rounds of intersection, mutation, evaluation, and evolution on some lineups using the genetic algorithm, or may be obtained based on real player data of the game, for example, a certain number of lineups may be selected from lineups used by game players as the initial lineup based on the real player data, or may be a lineup obtained by randomly selecting or selecting strength of the lineups (for example, may be determined based on a success rate or a best rate of real battles of the lineups) that satisfies a certain condition (for example, a lineup with strength within a certain strength range, or a lineup with strength against a certain strength threshold value).

Step S120: and executing at least one optimization operation aiming at each initial lineup in the initial lineup set, and determining a target lineup based on the optimized initial lineup set.

Because the formation fighting capacity of each initial formation is not necessarily high enough, if the initial formation is directly recommended to the player as the ladder formation, the experience of the player may be reduced. Based on this, the data processing method provided in the embodiment of the application, after the initialization lineup set is obtained, at least one optimization operation is performed on each initial lineup in the set, so as to improve the fighting capacity of the lineup, obtain the optimized lineup, determine the final target lineup based on each optimized lineup, determine the skyline lineup recommended to the player based on the determined target lineup, optionally, recommend the target lineups as the skyline lineup to the player, so that when the player carries out lineup construction by referring to the target lineups, the lifted lineup can have higher fighting capacity, and the use perception of the player is improved.

In practical application, the operation end condition for performing the optimization operation at least once for each initial lineup in the initial lineup set may be configured according to actual requirements. The embodiments of the present application are not limited. For example, the maximum iteration number of the optimization operation may be set, and if the number of times of performing the optimization operation on each initial lineup in the initial lineup set reaches the maximum iteration number, the optimization operation may be ended, where the initial lineup set at this time is the optimized initial lineup set. Optionally, the operation ending condition may also be relative to the initial lineup, for example, the operation ending condition may be that the lineup strength of a new initial lineup corresponding to the initial lineup is greater than and then equal to a certain threshold, and then, for each initial lineup, if the condition is satisfied, the optimization operation may not be performed on the lineup, and the new initial lineup corresponding to the initial lineup and satisfying the condition is the optimized lineup corresponding to the initial lineup. The operation ending condition can configure the maximum iteration times of the initial array capacity, and the optimization of the array capacity can be stopped after the optimization times of one initial array capacity reaches the iteration times.

After the optimized initial lineup set is obtained, the specific mode for determining the target lineup based on the optimized initial lineup set can be configured according to actual requirements. Optionally, determining the target lineup based on the optimized initial lineup set may include at least one of:

determining each array capacity in the optimized initial array capacity set as a target array capacity, namely directly providing the array capacity in the optimized initial array capacity set as a ladder array capacity for a player;

determining each array capacity of the optimized initial array capacity set, the array capacity strength of which meets set conditions, as a target array capacity, namely screening partial array capacities from the optimized initial array capacity set as the ladder array capacities;

obtaining a plurality of candidate recommended lineups, determining a target lineup from the candidate recommended lineups according to the fighting condition of each lineup in each candidate recommended lineup and the optimized initial lineup set, or carrying out at least one lineup adjustment on at least part of the candidate recommended lineups based on the fighting condition corresponding to each candidate recommended lineup, and taking the adjusted candidate recommended lineup and the unadjusted candidate recommended lineup as the target lineup.

The specific number of the finally determined target lineups may be configured according to actual requirements, for example, may be 100.

The candidate recommended lineup may be understood as a candidate skateboar lineup, and for a specific obtaining manner of the candidate recommended content, the embodiment of the present application is not limited, for example, a plurality of lineups may be constructed by a game planner according to a cognition of the game planner or a lineup with relatively strong fighting power selected from the plurality of lineups after a battle test of a certain scale is performed on the plurality of lineups. Optionally, the candidate recommended lineup may also be a lineup predicted by a trained neural network model. For example, a lineup matching requirement (e.g., a lineup including three heros each having two skills) for a target game application may be input into the neural network model, and a number of candidate recommended lineups may be generated by the neural network model based on all of the lineup elements in the game application.

For the method for determining the target lineup from the multiple candidate recommended lineups, before the skateladder lineup of the target game application is released, each candidate recommended lineup (such as the recommended lineup expected by the game plan) can be simulated and matched with the lineup obtained based on the method provided by the embodiment of the application (namely each lineup in the optimized initial lineup) respectively, and whether the candidate recommended lineup reaches the expected lineup strength is verified. If the strength is not up to the expectation, adjusting the game value (such as one or more of the virtual character or the virtual skill) to improve the strength of the candidate recommendation formation, issuing the game version after one or more times of game value adjustment, and pushing the candidate recommendation formation with the strength up to the expectation to the player.

In the embodiment of the present application, one optimization operation may include steps S121 to S125 as shown in fig. 1 for one initial lineup.

Step S121: determining a first array strength of the initial array;

step S122: and determining the array capacity elements to be replaced in the initial array capacity.

For an initial lineup, the lineup element to be replaced is at least one lineup element in the initial lineup, that is, each time the optimization operation may perform replacement of one or more lineup elements, if the replacement of multiple lineup elements is performed, the following step S123 may be performed for each lineup element to be replaced, or the multiple lineup elements to be replaced are taken as a whole, and the new lineup element corresponding to the whole is determined through step S123, for example, the number of the elements to be replaced is two, the new lineup element corresponding to each lineup element to be replaced may be determined in sequence, or the two lineup elements to be replaced are taken as a whole, and the two new lineup elements corresponding to the two lineup elements to be replaced are determined.

The selection method of the lineup elements to be replaced is not limited in the embodiment of the present application, and for example, one or more lineup elements in the initial lineup may be randomly selected as the lineup elements to be replaced.

Step S123: and determining new array capacity elements corresponding to the array capacity elements to be replaced from the candidate array capacity elements based on the array capacity elements reserved in the initial array capacity and the linkage coefficient between the candidate array capacity elements.

Step S124: and replacing the array capacity element to be replaced by adopting the new array capacity element, and determining the second array capacity strength of the replaced array capacity.

Step S125: and determining the lineup corresponding to the larger lineup intensity in the first lineup intensity and the second lineup intensity as a new initial lineup corresponding to the initial lineup in the initial lineup set.

The reserved lineup elements in one initial lineup refer to lineup elements in the initial lineup except lineup elements to be replaced. For example, an initial lineup includes 6 lineup elements, 1 lineup element is to be replaced, and the remaining lineup elements are the other 5 lineup elements.

Optionally, when replacing the lineup elements in the initial lineup, one optimization operation may be for one lineup element, that is, one lineup element is replaced by one optimization operation. For a lineup element to be replaced, each candidate lineup element corresponding to the lineup element may be a lineup element other than the lineup element to be replaced in each lineup element in the target game application. In addition, in order to avoid repeated lineup elements in the same lineup as much as possible, each candidate lineup element corresponding to one lineup element to be replaced may be a lineup element, other than the plurality of lineup elements included in the initial lineup, in each lineup element in the target game application.

Optionally, each time of the optimization operation may also be performed on a plurality of array capacity elements, for example, the array capacity elements to be replaced may be two, and two array capacity elements may be used as a whole, and two new array capacity elements corresponding to the whole are determined based on the linkage coefficients between the retained array capacity elements and the candidate array capacity elements corresponding to the whole. Accordingly, at this time, the whole corresponding one candidate lineup element is a plurality of candidate lineup elements (referred to as a candidate set). Optionally, the linkage coefficient between the candidate set and the reserved array-capacity element corresponding to the whole may be determined based on the linkage coefficient between each candidate array-capacity element and the reserved array-capacity element in the candidate set, for example, the sum of the linkage coefficients between each candidate array-capacity element and the reserved array-capacity element in the set may be determined as the linkage coefficient between the set and the reserved array-capacity element.

In addition, considering that in practical application, a game lineup may include a plurality of different types of lineup elements (for example, lineup elements including two types of virtual characters and virtual skills), in order to ensure that matching requirements of lineup before and after lineup element replacement do not change, each candidate lineup element corresponding to one lineup element to be replaced may be a lineup element belonging to the same type as the lineup element to be replaced in the target game application. If the lineup element to be replaced is a virtual skill, the corresponding candidate lineup element is also a virtual skill.

In the embodiment of the present application, the carrying coefficients between the formation elements characterize the fighting capacity that the combination between the formation elements can additionally generate, that is, when the formation elements are combined (existing in the same formation), in addition to the fighting capacity (such as skill effect) of the formation elements in the combination, the fighting capacity that the combination can additionally generate, that is, the fighting capacity of the combination is increased relative to the fighting capacity that each of the formation elements in the combination individually has. Every array element in the game application is used as an independent gene, the combination of array elements can be called as a continuous gene, the continuous coefficient corresponding to the continuous gene represents the enhancement relationship among the genes in the continuous gene, wherein the continuous coefficient and the enhancement relationship are in positive correlation, namely the larger the continuous coefficient is, the stronger the enhancement relationship among the genes in the corresponding continuous gene is represented, namely the larger the battle effectiveness which can be generated additionally is.

The continuous carrying coefficient between the array capacity elements can include but is not limited to the continuous carrying coefficient between two array capacity elements, and can also include the continuous carrying coefficient between more than two array capacity elements. That is to say, the new array capacity element that the array capacity element that is to be replaced corresponds is determined from each candidate array capacity element based on the continuous coefficient between array capacity element that is reserved in this initial array capacity and each candidate array capacity element, and to each candidate array capacity element, this continuous coefficient can include the continuous coefficient between at least two array capacity elements, can also include the continuous coefficient between a plurality of array capacity elements, and wherein, this at least two array capacity elements can include at least one element in candidate array capacity element and the above-mentioned reservation array capacity element.

As an alternative, the carry coefficient between the capacity elements may be a carry coefficient between two capacity elements in consideration of data processing efficiency in actual implementation, that is, the combination between the capacity elements may be two capacity elements.

As an example, assuming that the initialized carry coefficient between any two lineup elements in the target game application is 1, if two lineup elements (such as lineup elements a and B) have mutual enhancement relationship (which may be a enhancement effect on B, a enhancement effect on a, or both enhancement effects on each other), that is, when a and B are used in combination at the same time, that is, when a and B are simultaneously present in one lineup, a and B can generate extra fighting power, the carry coefficient between a and B is increased, for example, from 1 to 5, and this value of 5 can be used as the final carry coefficient between a and B.

Specifically, assuming that the above-mentioned lineup element a is skill a, and the lineup element B is skill B, the linkage coefficient between the skill a and the skill B represents the magnitude of the skill effect that can be additionally generated by the combination of a and B in addition to the skill effect of the skill a and the skill effect of the skill B when the two skills are simultaneously used.

After at least one array element in the initial array capacity is replaced based on the continuous carrying coefficient between the array capacity elements, in order to determine a new initial array capacity corresponding to the initial array capacity from the initial array capacity and the replaced array capacity, namely, whether the initial array capacity needs to be replaced by the replaced array capacity, the strength of the initial array capacity and the replaced array capacity needs to be evaluated, so that the array capacity with higher array capacity strength is used as the new initial array capacity, for example, if the first array capacity strength is greater than or equal to the second array capacity strength, the new initial array capacity is still the original initial array capacity, namely, the new initial array capacity is not replaced, and if the first array capacity strength is equal to or less than the second array capacity strength, the initial array capacity is replaced by the replaced array capacity, namely, the replaced array capacity is used as the new initial array capacity.

The embodiment of the present application is not limited to a specific determination method of the lineup strength of a lineup. It will be appreciated that the above-described manner of evaluating the capacity strength of the initial capacity and the capacity strength of the replaced capacity may be chosen in the same manner so that the capacity strengths of the two capacities are better comparable. Optionally, the strength of the lattice capacity of one lattice capacity may be implemented by using a trained neural network model, for example, a plurality of lattice capacity elements of one lattice capacity may be input into the neural network model, and the model inputs a prediction result capable of representing the strength of the lattice capacity. The specific representation mode of the lineup intensity is not limited in this embodiment, and may include, but is not limited to, a ratio of lineup or a ratio of dominance. For convenience of description, the strength of the lineup is characterized in terms of the goodness of the lineup in the following description.

Optionally, the data processing method may further include:

acquiring a reference lineup set, wherein the reference lineup set comprises a plurality of reference lineups;

the determining the first burst strength of the initial burst may include:

the initial lineup and each reference lineup in the reference lineup set are combated;

and determining a first array capacity strength of the initial array capacity based on the fighting results of the initial array capacity corresponding to the reference array capacities.

Accordingly, the determining the second capacity strength of the replaced capacity may include:

the replaced formation and each reference formation in the reference formation set are combated;

and determining a second formation strength of the replaced formation based on the fighting results of the replaced formation corresponding to the reference formations.

Similarly, each reference lineup may also include a plurality of lineup elements. It will be appreciated that the formation of the reference lineup should be the same as the formation of the original lineup so that the strength of the original lineup (or the replaced lineup) is more comparable to the strength of the reference lineup.

The reference lineup in the embodiment of the present application may also be referred to as a reference lineup, which is an evaluation reference for measuring the strength of the lineup of one lineup. The embodiments of the present application are not limited to the specific acquisition of the reference lineup, and may include, but are not limited to, acquiring the reference lineup in one or more of the manners listed above for acquiring the initial lineup.

Wherein, for each initial lineup, determining a first lineup intensity of the initial lineup based on the fight results of the initial lineup corresponding to the respective reference lineups comprises:

and determining the optimal rate of the initial lineup based on the fighting results of the initial lineup corresponding to the reference lineups, and taking the optimal rate of the initial lineup as the first lineup strength of the initial lineup.

Similarly, the optimal rate of the replaced lineup corresponding to each reference lineup may be determined based on the fighting results of the replaced lineup corresponding to each reference lineup, and the optimal rate may be determined as the second lineup strength of the replaced lineup.

That is, a lineup (initial lineup or replaced lineup) may be associated with the optimal rate of each reference lineup as the lineup strength of the lineup. Of course, besides the above-mentioned optimal rate, the frame rate of a frame or other index values of frame strength evaluation indexes may be used to measure the frame strength of a frame.

In the scheme provided by the embodiment of the application, the array capacity elements in the initial array capacity can be replaced based on the linkage coefficient between the array capacity elements, and whether the array capacity before replacement is replaced by the array capacity after replacement is determined based on the intensity of the array capacity before replacement and the intensity of the array capacity after replacement, so that the optimization of the initial array capacity in the initial array capacity set is realized. The scheme guides the evolution of the formation by utilizing the continuous carrying coefficients among the elements of the formation, realizes the automatic optimization of the formation, and continuously improves the fighting capacity of each formation in the initial formation set. Based on the method, the target formation with stronger fighting capacity can be obtained more quickly and accurately. In addition, the method can be used without manual intervention, the labor cost required to be consumed can be greatly reduced, and the generation efficiency of the target array capacity is improved. The method provided by the embodiment of the application better meets the requirement of practical application.

In an optional embodiment of the present application, an initial lineup includes at least two types of lineup elements, and each candidate lineup element corresponding to a lineup element to be replaced is a lineup element belonging to the same type as the lineup element to be replaced; for an initial lineup, the determining, based on the linkage coefficient between the lineup element retained in the initial lineup and each candidate lineup element, a new lineup element corresponding to the lineup element to be replaced from each candidate lineup element may include:

In practical applications, a game lineup in a game application may include one or more types of lineup elements, and the construction of the lineup is required to meet the lineup matching requirements of the game application. Therefore, when at least one element of the initial lineup is replaced, the initial lineup should be adjusted by using the same type of lineup element as the lineup element to be replaced. For example, if the lineup element to be replaced is a virtual character (a type of lineup element), then the new lineup element corresponding to the lineup element should also be a virtual character.

For one capacity element in one capacity, the associated capacity element of the capacity element in the capacity may be the capacity element having an association relationship with the capacity in each capacity element included in the capacity. And the criterion for judging whether the different array capacity elements have the association relation can be configured according to the requirement. The related lineup elements of one lineup element may include lineup elements having direct association with the lineup element, and may also include lineup elements having indirect association with the lineup element, wherein the lineup elements having indirect association with the lineup element may include lineup elements having direct association with the first related lineup element (lineup elements having direct association with the lineup element).

Optionally, the two lineup elements have an association relationship, which may mean that the two lineup elements have a binding relationship in one lineup, for example, one lineup element is collocated with another lineup element. For example, a lineup contains two types of lineup elements, namely virtual characters and virtual skills, wherein the virtual skills in the lineup are the skills that each virtual character in the lineup has, and then the virtual skills and the virtual characters for the virtual skills are lineup elements with an association relationship.

As an example, assuming that a lineup includes hero a (i.e. avatar) and skills a1 and a2 of hero a, and also includes skills B1 and B2 of hero B (i.e. avatar) and hero B, the associated lineup elements of skill a1 in the lineup include skill a1 and skill a2 for hero a, and skill a1 in the lineup include skill a (i.e. lineup elements having direct association with skill a 1) and also include skill a2 (i.e. lineup elements having indirect association with skill a 1).

For a candidate array capacity element corresponding to the array capacity element to be replaced, the first importance corresponding to the candidate array capacity element characterizes the importance degree of the candidate array capacity element in the array capacity after the replacement if the candidate array capacity element is adopted to replace the array capacity element to be replaced, and can also be understood as the size of the effect that the candidate array capacity element can play in the array capacity after the replacement or the improvement degree of the fighting capacity brought by the array capacity after the replacement. Because the company between the array capacity element has characterized the extra battle force that the combination between the array capacity element can produce, and the array capacity element that keeps is also certain array capacity element that exists in the array capacity after the replacement, consequently, can be based on the company between candidate array capacity element and the array capacity element that keeps and carry the coefficient, confirm the importance of candidate array capacity element, and can further be based on the importance of each candidate array capacity element, screen out new array capacity element and the array capacity element that keeps from each candidate array capacity element and constitute the array capacity after the replacement.

Optionally, for a candidate lineup element, the sum or product of the carry coefficient between the first lineup element and the candidate lineup element and the carry coefficient between the second lineup element and the candidate lineup element may be used as the corresponding importance of the candidate lineup element. Optionally, in order to make the importance and the carry-on coefficient have a positive correlation, when the product is used as a representation of the importance, the carry-on coefficient between the array elements may be a non-zero integer.

When determining a new lineup element based on the first importance of each candidate lineup element, normalization processing may be performed on the first importance of each candidate lineup element, for example, after the sum is calculated, the first importance of each candidate lineup element may be normalized to a value between [0 and 1] based on the sum corresponding to each candidate lineup element, and the normalized value may be used as a probability that the candidate lineup element is selected as the new lineup element. For example, assuming there are three candidate lineup elements corresponding to the above sums of 2, 3, and 5, respectively, then the probability that each of the three candidate elements corresponds may be 0.2, 0.3, and 0.5.

After determining the probability corresponding to each candidate lineup element of the lineup element to be replaced, determining a new lineup element corresponding to the lineup element to be replaced from each candidate lineup element, which may include:

and taking the probability corresponding to each candidate array capacity element as the random screening probability of each candidate array capacity element selected as a new array capacity element, and randomly selecting the new array capacity element from each candidate array capacity element.

That is, a random mode according to the probability can be adopted to screen new array capacity elements from the candidate array capacity elements, the probability that the new array capacity elements are randomly selected is relatively higher if the probability is higher, and the new array capacity elements are used for replacing the corresponding array capacity elements to be replaced, so that the replaced array capacity is obtained.

Of course, in addition to the random screening, other screening may also be used according to the probability corresponding to each candidate array capacity element, for example, the candidate array capacity element corresponding to the maximum probability may be selected as the new array capacity element.

It can be understood that the carrying coefficients between the candidate array element and the reserved array element may include at least one of the carrying coefficients between the candidate array element and the first array element, or the carrying coefficients between the candidate array element and the second array element, or may be carrying coefficients between the candidate array element and each array element in the reserved array element, that is, a new replacement element may be determined from each candidate array element based on the carrying coefficients between each candidate array element and each array element in the reserved array element.

In an alternative embodiment of the present application, the at least two types of lineup elements in one initial lineup include two types of lineup elements of virtual roles and virtual skills; if the lineup element to be replaced is a virtual character, the related lineup element of the virtual character comprises virtual skills of the virtual character; if the lineup element to be replaced is a virtual skill, the related lineup element of the virtual skill comprises at least one of a target virtual character with the virtual skill or other virtual skills, except the virtual skill, of the target virtual character.

Correspondingly, if the lineup element to be replaced in an initial lineup is a virtual character (called a first character), and the candidate lineup element corresponding to the lineup element is also a virtual character (called a second character), the linkage coefficient between the second character and the lineup element retained in the initial lineup may include the linkage coefficient between the second character and the virtual character in the retained lineup element of the initial lineup, or at least one of the linkage coefficient between the virtual skill possessed by the first character and the second character.

If the element of the lineup to be replaced in the initial lineup is a virtual skill (referred to as a first skill), and the candidate lineup element corresponding to the element of the lineup is also a virtual skill (referred to as a second skill), the carry coefficient between the second character and the element of the lineup reserved in the initial lineup may include at least one of a carry coefficient between the virtual character with the first skill and the second skill, or a carry coefficient between other virtual skills possessed by the virtual character with the first skill and the second skill.

Correspond a formation element in an initial formation, when regard this formation element as a formation element of waiting to replace, because the combination that the formation element has been represented to the ability of company between the formation element can bring extra promotion to the fighting capacity of formation, then, if the probability that this candidate formation element that the coefficient of company between a candidate formation element and other elements in this formation (that is the formation element that remains) confirms is corresponding is bigger for this candidate formation element, just says that if this candidate formation element replaces this formation element of waiting to replace, the formation intensity of formation after the replacement should theoretically be can have big promotion. In view of this, the above alternative provided in this embodiment of the present application may determine a new lineup element from each candidate lineup element based on the probability corresponding to each candidate lineup element.

After treating replacement lineup element and replacing based on new lineup element, though theoretically the lineup intensity of the lineup after the replacement should be promoted, in actual fight, the actual fight condition of every lineup element has many uncertain factors, therefore, after the replacement, can be based on the first lineup intensity of initial lineup and the second lineup intensity of the lineup after the replacement that this initial lineup corresponds, whether this initial lineup in the initial lineup set will be replaced by the lineup after the replacement is confirmed, thereby what make to keep in the optimized lineup set is that the lineup intensity is each lineup stronger relatively.

It can be understood that, in practical applications, the above optimization operation may be performed one or more times on an initial lineup in the initial lineup, and if the optimization operation is performed multiple times, for the initial lineup, the first optimization operation is directed to the initial lineup, and the subsequent optimization operation is directed to a new initial lineup corresponding to the initial lineup obtained by the last optimization operation, where the new initial lineup may be the initial lineup or may be a replaced lineup.

In an optional embodiment of the present application, in the step S122, for an initial lineup, determining lineup elements to be replaced in the initial lineup may include:

In this alternative, for each array capacity element in the initial array capacity, the array capacity element to be replaced in the initial array capacity may be determined based on the carry coefficient between each array capacity element and other array capacity elements except the array capacity element in the initial array capacity. Such as may be implemented in the manner described above in which the second importance of each lineup element is determined. For a second importance in this alternative, reference may be made to the description of the first importance hereinbefore, the principles of both being similar, except that one is for each capacity element in the initial capacity and one is for the candidate capacity element. By adopting the scheme, the replaced array capacity has better array capacity element composition, and the array capacity is more quickly optimized.

In this alternative, since the lineup elements to be replaced, that is, the lineup elements to be replaced are determined, when the lineup elements to be replaced are determined based on the second importance of each lineup element in the initial lineup, the greater the second importance of the lineup elements is, the smaller the probability that the lineup elements are selected as the lineup elements to be replaced is. For example, the second importance of each array element may be normalized to a value in the range of [0,1], each normalized value is used as the probability that the array element is not selected as the array element to be replaced, the array element to be replaced is determined based on the probability corresponding to each array element, for example, the array element with the minimum probability is selected as the array element to be replaced, or the normalized value corresponding to each array element is converted into 1 to subtract the normalized value, the converted value corresponding to each array element is used as the random selection probability of each array element, and the array element to be replaced is determined from each array element by adopting a random screening method.

In an optional embodiment of the present application, the plurality of lineup elements in one initial lineup include at least two types of lineup elements, for one initial lineup, each time the optimization operation takes one type of lineup element in the initial lineup as a lineup element to be replaced, and each type of lineup element in the initial lineup corresponds to at least one optimization operation.

That is, one type of lineup element in the initial lineup may be replaced each time an optimization operation is performed. Each type in the initial lineup corresponds to at least one optimization operation, that is, the number of times of performing the optimization operation on the initial lineup is not less than the number of types of lineup elements contained in the lineup, for example, two types of lineup elements, i.e., s1 and s2, are contained in the initial lineup, then the optimization operation may be performed at least twice, at least one optimization operation is performed on at least one lineup element of the s1 type in the initial lineup, and at least one optimization operation is performed on at least one lineup element of the s2 type.

By adopting the scheme, the array capacity elements of various types in the initial array capacity can be respectively tried to be replaced, and whether the array capacity before replacement is replaced by the array capacity after replacement is determined by evaluating the array capacity intensity before and after replacement. For example, the lineup elements of the at least two lineups include two types of lineup elements, namely a virtual character and a virtual skill, and at least one virtual character in the initial lineup can be optimized at least once, at this time, one optimization operation is to replace the at least one virtual character with another virtual character to obtain a replaced lineup, and whether to use the replaced lineup as a new initial lineup is determined based on the lineup strengths of the initial lineup and the replaced lineup. If the optimization operation is subsequently performed again on the initial lineup, the above-mentioned actions are performed again based on the new initial lineup.

In practical application, when the above optimization operations are respectively executed on multiple types of array capacity elements in the initial array capacity, which type of array capacity element is optimized first, and which type of array capacity element is optimized later, which embodiment of the present application is not limited. Optionally, optimization operations may be performed on various types of array capacity elements in sequence according to a set type sequence. For example, one lineup contains two types of lineup elements, the optimization operation may be performed on one lineup element of one type (first type) (that is, the lineup element is used as a lineup element to be replaced), after a new initial lineup is obtained, the optimization operation may be performed on one lineup element of the other type (second type) in the lineup based on the new initial lineup, and the next optimization operation may perform the optimization operation on one lineup element of the first type again.

The operation ending condition for performing the above optimization operation for each lineup in the initial lineup set may refer to the description in the foregoing, and will not be repeated here.

For the data processing method provided in the embodiment of the present application, in actual implementation, the construction timing and the acquisition mode of each lineup in the initial lineup set and the reference lineup set may be configured as required, and the present application is not limited at all. For example, the server or the terminal device may pre-construct the initial lineup set and the reference lineup set, and store the initial lineup set and the reference lineup set in the corresponding databases, and when the target lineup needs to be determined, the server or the terminal device may directly retrieve the initial lineup set and the reference lineup set from the databases. Certainly, the server may pre-construct the initial lineup set and the reference lineup set, and store the initial lineup set and the reference lineup set in the database, when the terminal device executes the method, the terminal device may send a corresponding data acquisition request to the server, and the server may, according to the request, call the pre-stored reference lineup set and the initial lineup set from the database to be combined, and send the combined result to the terminal device. Of course, the server or the terminal device may also correspondingly construct the initial lineup set and the reference lineup set when the target lineup needs to be generated, that is, when the target lineup generation instruction is obtained.

Similarly, for the calculation of the linkage coefficients between different lineup elements in the target game application, the server or the terminal device may calculate the linkage coefficients between the lineup elements in all the lineup elements in the target game application in advance, and store the linkage coefficients into the corresponding database, when the target lineup needs to be generated, read the linkage coefficients between the required lineup elements from the database, where the linkage coefficients between the required lineup elements are the linkage coefficients between the remaining lineup elements and the candidate lineup elements in the initial lineup to be applied when the target lineup is determined. Of course, when the target lineup generation instruction is acquired, the linkage coefficient between the reserved lineup elements and the candidate lineup elements in the initial lineup may be calculated.

Alternatively, the carry-along coefficient between any (at least two) lineup elements in the target game application may be determined based on configuration information of the lineup elements in the application.

Specifically, the linkage coefficient between the formation elements in the target game application is determined by the following method:

acquiring attribute information of each array element;

Wherein, the attribute information of the lineup element in the target game application can be obtained by the following method:

and obtaining the attribute information of each lineup element based on the configuration information of each lineup element.

In an actual application, the application configuration information of the application may be obtained by reading an application configuration file of the target game application, for example, the configuration information of all the lineup elements of the target game application of the version may be obtained based on the application version (i.e., game version) of the target game application, for example, the configuration information of all the virtual characters and the configuration information of all the virtual skills in the target game application of the version may be obtained, and the attribute information of each virtual character and the attribute information of each virtual skill may be extracted based on the obtained configuration information.

For the virtual skill, the configuration information may include skill description information of the virtual skill, and the attribute information of the virtual skill, such as one or more of a skill type, a skill effect, or a skill enhancement condition, may be extracted from the description information by performing syntactic analysis on the skill description information of the virtual skill.

The data processing method provided by the embodiment of the application obtains the attribute information of each formation element in the game based on obtaining the application configuration information in the target game application, and can determine the linkage coefficient between different formation elements based on the matching degree between the attribute information of different formation elements, and on the basis, can guide the evolution of the initial formation based on the linkage coefficient between the formation elements, and automatically generate the required target formation. Based on the scheme, the target formation can be generated quickly and efficiently, and the obtained target formation has higher fighting capacity (namely, the formation strength is higher), so that the high ladder formation with higher fighting capacity can be recommended for the player applied to the target game based on the determined target formation, the game player can match the own game formation with the high ladder formation, and based on the method, the game perception of the player can be effectively improved.

For a lineup element, the attribute information of the lineup element may include one or more items of attribute information, and the linkage coefficient between the lineup elements is determined based on the matching degree between the attribute information of each lineup element.

In practical application, the matching degree of which attribute information or the matching degrees of which attribute information are specifically adopted to determine the linkage coefficient between the array-content elements, and the linkage coefficient can be configured according to the requirements of practical application and can be determined according to the matching degree between at least one item of specified attribute information. Optionally, for the determination of the linkage coefficients between different types of formation elements, the designated attribute information may be the same or different, and this embodiment of the present application is not limited, for example, the configuration may be configured according to the application requirements and the application configuration of the target game application.

Optionally, one lineup element may be a virtual character or a virtual skill, and for one virtual character, the attribute information of the lineup element may include at least one of a lineup, a character type or a trip of the virtual character to which the virtual character belongs; for a virtual skill, the attribute information of the lineup element may include at least one of a skill type, a skill effect, or a skill enhancement condition of the virtual skill.

Wherein the skill enhancement condition of a skill comprises a condition for enhancing the skill effect of the skill. For example, a virtual skill would have the effect of "causing 50% harm to an enemy and applying silence," which may be 10% higher if the enemy is currently intoxicated, and the effect of the virtual skill would include silence, with the condition of increased skill being intoxication.

The lineup elements (of a type, which specific lineup elements are) in a gaming application may be different for different gaming applications. The embodiment of the present application is not limited to the division of the types of the lineup elements (e.g., virtual characters and virtual skills) in a game application, for example, the types of the virtual characters in the game application may include force, intelligence and assistance, and the division of the lineup to which the virtual characters belong is not limited.

The determination method of the matching degree (such as whether matching is performed or not, and the size of the matching degree during matching can also be included) between the attribute information of different lineup elements can also be flexibly configured according to the actual application requirements. Optionally, the greater the matching degree between the attribute information of different formation elements, the greater the linkage coefficient between the formation elements may be. Of course, for different combinations of formation elements, different ways of determining the carry-together coefficients between formation elements may also be configured. For example, the manner of determining the linkage coefficient between the virtual character and the virtual skill may be different from the manner of determining the linkage coefficient between the virtual character and the virtual skill.

As an alternative, the determining the linkage coefficient between the array elements according to the matching degree between the attribute information of the array elements includes:

Optionally, in practical applications, any two array elements may have an initialized carry coefficient (e.g., may be 0,1, or other values). For two virtual characters, if the roles of the two virtual characters are the same, the connection coefficient between the two virtual characters can be increased, and if the constraints of the two virtual characters are matched, including the same constraint, the connection coefficient between the two virtual characters can be increased. For two virtual skills, if the skill effect of one of the two virtual skills satisfies the skill enhancement condition of the other, the carry factor between the two virtual skills may be increased. For a virtual character and a virtual skill, the matching of the type of the virtual character and the type of the virtual skill means that the virtual character of the character type can possess the skill of the skill type, and if the character type of a virtual character and the skill type of a virtual skill are mutually configured, the linkage coefficient between the virtual character and the virtual skill can be increased.

It is understood that the above-described scheme for determining the linkage coefficient between two array capacity elements is explained by using the linkage coefficient between two array capacity elements, and in practical applications, in addition to the linkage coefficient between two array capacity elements, the linkage coefficient between more than two array capacity elements may also be considered. For example, a line volume may include three heros, for example, A, B and C, the first carrying coefficient between two heros may be determined based on the matching degree between the attribute information of each two heros in the three heros, the matching degree between the attribute information of the three heros may be further determined, and whether the first carrying coefficient between two heros that has been determined is adjusted is determined according to the matching degree of the three heros, for example, a trip in a game requires that three designated heros be included in the line volume at the same time, if A, B and C are exactly the three designated heros, the first carrying coefficients between two heros in A, B and C are respectively increased, and the increased carrying coefficients are used as the final carrying coefficients between two heros.

The method provided by the embodiment of the application can be applied to any game application (namely, a target game application), the target formation, namely, the skateladder formation, corresponding to the game application is determined before the game application is online, and the released skateladder formation of the game application can be optimized, namely, the skateladder formation is updated. The target game application may be a game running in the mobile terminal, may be a game running in the fixed terminal, and may also be a cloud game, an applet game, or the like. Correspondingly, each lineup element is a lineup element contained in the game lineup in the target game application,

in addition, in actual application, a capacity constraint condition of the initial capacity can be configured, for example, the constraint condition may be that a repeated virtual character cannot exist in a plurality of virtual characters in one initial capacity, and based on the constraint condition, the capacity in the optimized initial capacity set can cover most virtual characters in the game to the maximum extent, so that most virtual characters in the game can correspond to at least one optimized capacity, and an actual application scenario is better satisfied. For example, each lineup in the optimized initial lineup combination can be directly used as a skateladder lineup, the skateladder lineup can contain the lineup corresponding to each virtual character as much as possible, and after the skateladder lineups are recommended to players, each player can find the lineup containing one or some designated virtual characters from the skateladder lineups and match the own game lineup based on the found lineup.

The method provided by the embodiment of the application can be applied to any game application needing to automatically generate the game with higher fighting capacity, and can include but is not limited to a simulation game, namely SG. To explain the method provided by the present application in more detail, an alternative embodiment of the method is described below, taking SG as an example, where a game lineup (initial lineup, reference lineup) includes three heros, each hero being configured with two virtual skills.

Fig. 2 is a schematic diagram illustrating an application scenario of the data processing method according to the embodiment of the present application. As shown in fig. 2, the application scenario includes a terminal device 11, a terminal device 12, an operation server 21, and a game server 22. The terminal device 11 is a terminal device of an operation management client running a target game application, and the operation management client may be oriented to a manager of the target game application (such as a research and development staff, a planning staff, or other background operators with operation authority), and the manager may trigger an operation of generating a target lineup (that is, a ladder lineup) of the target game application through the operation management client. The terminal device 12 may be a player client of a target gaming application, through which a player may build a battle lineup using virtual roles and virtual skills. The operation server 21 may be an operation management server of the target game application, and the game server 22 is a server that communicates with the player client and provides game support for the player client. The operation server 21 and the game server 22 may be the same server or may be different servers.

The terminal device 11 may communicate with the operation server 21 through a network, trigger the operation server 21 to generate an elevator lineup, the operation server 21 may communicate with the game server 22, send the elevator lineup to the game server 22, the game server 22 sends the elevator lineup to the terminal device 12 of the game player, and display the elevator lineup to the game player through a player client on the terminal device, for example, when the player views the elevator lineup, the elevator lineup is displayed to the game player in a list form, for example, the player may display the elevator lineup according to the lineup strength of each lineup in the elevator lineup, or the elevator lineup including the lineups is preferentially displayed to the player based on a virtual character possessed by the current game player or one or more virtual characters already selected.

An alternative embodiment of the method provided in the present application is described below with reference to the schematic application scenario shown in fig. 2, and as shown in fig. 3, the method may mainly include the following steps.

Step S10: and reading the configuration file.

This step is used to read the configuration document (application configuration information) of the target game application, obtain a list of heroes and skills that can be used by the current application version of the target game application, and obtain detailed information of each hero and skill (i.e., attribute information of each lineup element).

Specifically, the operation server 21 may store application data of a plurality of game applications, and the application data may be, but is not limited to, data such as an application installation package and an application configuration document. The running server 21 may obtain attribute information, that is, the above-mentioned detail information, of each lineup element in a certain target game application by reading a configuration document of the target game application when receiving an skyline lineup generation instruction for the target game application triggered by an administrator through the operation management client. Of course, the operation server 21 may also obtain the attribute information of each lineup element in each game application by reading the configuration document of each game application in advance and store the attribute information in the corresponding database. When receiving an elevator formation generation instruction of a manager for a certain target game application, the attribute information of each formation element of the target game application can be scheduled from the database.

Alternatively, the above step S10 may include steps S11 to S14 as shown in fig. 4.

Step S11: and inputting the configuration file, namely acquiring the configuration document.

Step S12: an optional hero and skill list is read.

After obtaining the configuration document of the current application version of the target game application, all the optional heroes and skills (i.e. supported in the current application version) can be read from the configuration document to form a hero list and a skill list, that is, all the supported heroes and skills (specifically, identifiers of the heroes and skills, such as names of the heroes and the skills) can be obtained.

Step S13: hero details are read.

Step S14: reading skill details.

It is understood that the execution order of step S13 and step S14 may be exchanged, or may be executed in parallel.

For step S13, attribute information such as the position, type, trip, etc. of each hero may be sequentially read from the configuration file based on the obtained hero list. For example, game play in target game applications includes wei, shu, wu and wu, hero types include three hero types including force, intelligence and assistance, hero trips may include various trips such as F1 (trip name), F2, F3 and the like. For each hero in the hero list, the configuration information of the hero in the configuration file can be read to obtain each item of attribute information of the hero, namely hero details.

Similarly, for step S14, the type and skill description of each skill may be read from the configuration file in turn according to the skill list, and other attribute information of the skill may be obtained by analyzing the skill description of the skill. For example, the skill types in the target gaming application may include three skill types, force, intelligence, and assistance. By performing syntactic analysis on the skill description of each skill, the skill effect generated by the skill and the skill enhancement condition can be extracted. For example, skills effects and enhancements in targeted gaming applications include intoxication, incineration, thunderstorm, flooding, wind handle, silence, instrumental, exhaustion, vertigo, pedicure, cynicism, contraindication, and the like. As an example, assuming a skill of a skill is described as "causing 50% injury to an enemy and applying silence, if the enemy is in a poisoned state, the injury is increased by 10%", the resulting effect of the skill is silence, and the enhancing condition is poisoning.

Wherein a skill effect of one skill may be a skill enhancement condition of another skill, that is, a skill enhancement condition of one skill may be the presence of another skill effect.

The hero details information of each selectable hero and skill details information of each selectable skill in the target game application, that is, details of the output hero and skill shown in fig. 4, can be obtained through the above steps S11 to S14.

Step S20: and excavating the continuous gene.

This step is used to determine the carry-together coefficient between the lineup elements in the target gaming application. In this application scenario, the linkage coefficient between different array elements is described by taking the linkage coefficient between two array elements as an example. The carrying coefficients between different elements of the formation include the carrying coefficients between heroes and heroes, the carrying coefficients between heroes and skills, and the carrying coefficients between skills and skills in all the elements of the formation of the target game application.

Specifically, in the step, whether the hero and hero, hero and skill, and skill have enhancement relations can be judged respectively according to the detail information of each hero and skill read from the configuration file, and a linkage gene can be found to obtain a linkage coefficient between the elements of the formation. Similarly, the determination of the linkage coefficient between the lattice content elements may be completed in advance by the operation server 21, or may be performed after the generation instruction of the ladder lattice content is obtained. Optionally, the determination of the linkage coefficient between the lattice element in the application scenario may include steps S21 to S23 as shown in fig. 5, and the implementation of step S23 in step S21 is based on the details information of each hero and skill obtained in step S10 (i.e., the details of the input hero and skill as shown in fig. 5).

Step S21: and excavating the mutual carrying (namely the mutual carrying coefficient) between the hero and the hero.

Alternatively, a two-dimensional table of hero and hero may be initialized first, each value in the table representing the carry coefficient between hero and hero, wherein the carry coefficient between different heros may be initialized to 1 and the carry coefficient between the same hero may be initialized to 0. Then, the carrying coefficient between heroes can be increased according to marketing, for example, hero a and hero B both belong to the welfare country, and then the carrying coefficient between the heroes can be increased by a first preset value, for example, 2 can be added. The carrying coefficient between the hero can be increased according to a constraint, for example, the hero C, the hero D and the hero E correspond to a constraint, and then the carrying coefficient between the three heros can be increased by a second preset value, for example, 4 can be added, for example, the carrying coefficient between every two heros in the three heros can be increased by 4.

Optionally, the final mutual coefficient between any two heros may be determined according to the matching degree of each item of attribute information of the two heros, for example, the sum (or product) of the initialized mutual coefficient of the two heros and the preset value corresponding to the mutually matched attribute information in each item of attribute information of the two heros may be used as the final mutual coefficient between the two heros. For example, the initial mutual coefficient between hero a and hero B is 1, hero a and hero B belong to the same formation (i.e. formation are configured with each other), and hero a and hero B belong to the same structural element of the same trip, and if the preset value corresponding to the formation is 2 and the preset value corresponding to the trip is 4, the mutual coefficient before hero a and application B can be determined to be 1+2+4 to 7.

Step S22: digging the connection between hero and skill.

For the mining of the mutual coefficient between hero and skill, a two-dimensional table of hero and skill can be initialized, each value in the table represents the mutual coefficient between hero and skill, for example, the mutual coefficient between each hero and each skill can be initialized to 1. The portability factor between hero and skill can then be adjusted according to the degree of match between hero type (e.g. force, intelligence, assistance) and skill type (e.g. force, intelligence, assistance).

As an example, if the hero type is the same as the skill type, the carry-over factor between hero and skill may be increased by a third preset value, such as 4 may be added. For example, if the hero type of a hero is force and the skill type of a skill is force, then the carrying factor between the hero and the skill can be adjusted to 5. If the hero type and the skill type are different, the carry factor between hero and skill may be reduced by a fourth predetermined value, such as may be reduced by 1, e.g. the hero type of a hero is force and a skill type is intelligence, then the carry factor between hero and the skill is adjusted to 0, and the carry factor between hero and the skill is also 0, e.g. if the hero type of a hero is intelligence and a skill type of a skill is force. Optionally, the carry coefficient between any two array elements is at least 0, i.e. a non-negative number.

Step S23: and the digging skills are carried together.

And (5) digging the linkage coefficient between skills. Similarly, a two-dimensional table of skills and skills may be initialized, each value in the table represents a carry coefficient between skills and skills, carry coefficients between different skills may be initialized to 1, and carry coefficients between the same skills may be initialized to 0. Then, the carry-over factor between skills can be adjusted according to the producing effect (i.e. skill effect) and the enhancing condition of the skills, for example, if one skill needs to enhance the injury under the poisoning condition of the enemy, and the other skill can apply poisoning to the enemy, the carry-over factor of the two skills can be increased by a fifth preset value, such as 8.

It is understood that, in the implementation application, the execution sequence of the three steps S21 to S23 may not be limited, and may also be executed simultaneously and in parallel.

In practical application, whether the attribute information of hero and hero, the attribute information of hero and skill, and the attribute information of skill and skill are matched with each other or not is judged, and which attribute information or attribute information is adopted for judgment can be configured according to application configuration information such as practical application requirements, the relation between the formation elements in the target game application, the playing skills of different formation elements in the game formation, the generated functions, the properties of the formation elements, the possibility of matching and using different formation elements, the matching and using limit conditions and the like.

For example, in some game applications, if the skills and skills are linked genes (i.e., enhancement of skill effect can be generated), the fighting capacity (i.e., the degree to which the theory can enhance the strength of lineup) that can be additionally generated by the linked genes is stronger than the fighting capacity that can be generated by the linked genes between heroes and heroes, the corresponding increase range (i.e., the preset value) of the linked coefficients between skills and heroes may be greater than the increase range of the linked coefficients between heroes and heroes.

The linkage coefficient between hero and hero, the linkage coefficient between hero and skill, and the linkage coefficient before skill and skill (corresponding to the output linkage gene in fig. 5) in the target game application can be obtained through the above steps S21 to S23, and then the optimization of formation can be guided based on the linkage coefficient between formation elements.

Similarly, the step S20 may be executed in advance by the operation server 21, and store the obtained linkage coefficients between every two lattice elements in a corresponding database, and if necessary, retrieve the linkage coefficients before the required lattice element from the database. Of course, the operation may be executed when the generation instruction of the ladder array is acquired.

Step S30: and (4) carrying out formation optimization, namely constructing an initial formation set and optimizing the initial formation to obtain the ladder formation based on the optimized initial formation set.

In the application scenario, each array capacity in the optimized initial array capacity set can be used as an attic ladder array capacity. Optionally, the initial lineup and the reference lineup may be generated by using information (hero list, skill list, lineup collocation requirement, etc.) of the configuration file, and then the lineup may be subjected to multiple rounds of adjustment, evaluation and selection by using the continuous gene, so as to obtain the skateladder lineup of the current game version.

Fig. 6 is a schematic flow chart of an alternative formation optimization manner provided by the embodiment of the present application, which is implemented based on the mutual coefficient between each formation element in the target game application and the formation element obtained in step S20, that is, the input of step S30 is the hero list, the skill list, and the mutual coefficient between the formation elements (corresponding to the input hero skill list and the mutual coefficient shown in fig. 6). As shown in fig. 6, this method may specifically include the following steps S31 to S36.

Step S31: and generating a lineup.

Optionally, 500 initial lineups (initial lineup sets) and 5000 reference lineups (reference lineup sets) are generated from the hero and skill lists. Assuming that each line comprises three heros, each hero carries two skills, H₁S₁₁S₁₂H₂S₂₁S₂₂H₃S₃₁S₃₂，H_iDenotes the ith hero, S_ijIndicating the jth skill the ith hero has.

The initial lineup and the reference lineup may be generated in the same manner or different manners, for example, a hero may be randomly selected at each hero position, and then a same type of skill may be randomly selected at the corresponding skill position according to the type of hero. The hero and skill that is not repeated in the same lineup can be agreed upon in a random process. The initial formation forms a ladder formation after a plurality of rounds of evolution, and the reference formation is used for evaluating the strength of the formation.

Step S32: and adjusting hero.

In this step, for each initial lineup, one hero in the lineup (i.e. the lineup element to be replaced, which may also be referred to as the adjusted hero) may be randomly selected, and replaced with another hero according to the linked gene, which may be implemented as follows:

1) initializing an array with the length of hero number (the number of all heros in the target game application), wherein the initial value is 0;

2) adding the carrying coefficients of the other two heros (namely the reserved array capacity elements) in the array to the other heros (candidate array capacity elements) into the array;

3) adding the carrying coefficient of the skill of the adjusted hero in the lineup to other heros (candidate lineup elements) into the array;

4) and taking the value (namely the first importance or the normalized importance) in the array as the probability of selecting each hero, and randomly selecting one hero to replace the adjusted hero to obtain the replaced lineup.

Each hero in the target game application (optionally, each hero in all heroes in the application except the hero contained in the initial capacity, or all heroes in the application, and the corresponding value of three heroes in the initial capacity in the above array can be directly set to 0) can be used as a candidate, and the importance of each candidate hero can be calculated through the above steps 2) and 3).

Then, the above value corresponding to each hero can be used as the probability that the hero is selected, a new hero corresponding to the adjusted hero is determined by adopting a random selection mode, and the adjusted hero is replaced by the new hero.

Step S33: and evaluating the formation.

And (3) competing each newly generated lineup (namely the replaced lineup corresponding to each initial lineup) with all reference lineups, and calculating the optimal rate of each newly generated lineup to be used as the strength of the newly generated lineup. And the strength of the front and the back array volumes of hero is adjusted in a contrast way, and the higher strength is reserved.

Step S34: adjusting the skill.

In this step, for each initial lineup (in this application scenario, the initial lineup at this time is each lineup with higher strength that has been kept after adjustment), one skill in the lineup may be randomly selected, and another skill is replaced according to the linked gene, and specifically, the following method may be adopted:

1) initializing a number of sets of length the number of skills (which may be the number of all skills in the target game application), the initial value being 0;

2) adding the carrying coefficients of the hero carrying the skill in the lineup (such as a martial force, i.e. hero with influence type of force), and other skills (candidate lineup elements) to the array;

3) adding the carrying coefficient of another skill to other skills (candidate formation elements) of the hero carrying the skill in the formation to the array;

4) the value in the array (the importance of the skill) is taken as the probability of each skill, and one skill is randomly selected to replace the adjusted skill.

Similarly, the importance of each candidate skill may be calculated by the above steps 2) and 3) by taking each skill in the target game application (which may be the individual skills in the target game application except for the skills contained in the initial lineup, or may be all the skills in the application, and directly setting the value corresponding to the 6 skills in the initial lineup in the above array to be 0), and specifically, for a candidate skill, the importance of the candidate skill may be obtained by adding the coefficient of co-existence of the adjusted skill in the lineup to the candidate skill and the coefficient of co-existence of the hero to the candidate skill.

Then, the value corresponding to each skill can be used as the probability that the skill is selected, a new skill corresponding to the adjusted hero can be determined by adopting a random selection mode, and the adjusted skill can be replaced by the new skill.

Step S35: and evaluating the formation.

This step is the same as step S33, and for each lineup, the strength of the two lineups before and after the adjustment of the skill is compared, and the higher one of the strengths is retained.

Step S36: and judging the condition, namely judging whether the end condition of the optimization operation is met.

Optionally, the maximum iteration number of the array capacity optimization may be set, and if the maximum iteration number is reached, the process stops, and the finally reserved 500 array capacities (i.e., each array capacity in the adjusted initial array capacity set) are used as the ladder array capacity, and if the maximum iteration number is not reached, the process returns to S32, and the optimization operation is continuously performed on each adjusted array capacity until the maximum iteration number is reached.

It can be seen that, in the application scenario, each game lineup includes two types of lineup elements, namely hero and character, in an embodiment of the scenario, the operation of adjusting and evaluating the two types of elements in each of the 500 lineups is regarded as an optimization operation, for example, the maximum number of iterations is 3, after performing hero adjustment, skill adjustment and lineup evaluation 3 times on each initial lineup, the above condition is satisfied, and the operation may be ended, so as to obtain the finally reserved 500 ladder lineups (corresponding to the output ladder lineup in fig. 6). Of course, in practical applications, the operation of performing one adjustment of a lineup element (such as hero or skill), lineup evaluation, and holding a strong lineup on one lineup may also be regarded as one optimization operation, or the operation of performing one adjustment of a lineup element (such as hero or skill), lineup evaluation, and holding a strong lineup on each lineup may also be regarded as one optimization operation. Accordingly, the configuration of the operation termination condition (e.g., reaching the maximum number of iterations described above) may also be adjusted accordingly.

After obtaining the skyline lineup through continuous lineup optimization, the operation server 21 may send the 500 lineups to the game server 22, and the game server 22 pushes the skyline lineup to the terminal devices 12 of the players, so that the players can use the skyline lineup as a reference for lineup matching.

The data processing method provided by the embodiment of the application can be used for mining the continuous gene in the game from the configuration file based on the game, guiding the formation evolution by using the continuous gene, automatically generating the skateladder formation, ensuring that the skateladder formation has higher optimal flatness and can cover most of heros, and can be applied to but not limited to strategy simulation games with heros and skill combination formation. In addition, the method can provide effective reference data for the game planner to adjust the game value.

Based on the same principle as the data processing method provided by the present application, an embodiment of the present application further provides a data processing apparatus, and as shown in fig. 7, the data processing apparatus 100 may include an initial lineup obtaining module 110 and a target lineup determining module 120. Wherein:

determining a first array strength of the initial array;

The apparatus of the embodiment of the present application may execute the method provided by the embodiment of the present application, and the implementation principle is similar, the actions executed by the modules in the apparatus of the embodiments of the present application correspond to the steps in the method of the embodiments of the present application, and for the detailed function description and the effective effect of the modules of the apparatus, reference may be specifically made to the description in the corresponding method shown in the foregoing, and details are not repeated here.

The linkage coefficient determining module may be a module included in the data processing apparatus, or may be a module in another apparatus, where the determination operation of the linkage coefficient between the array elements is executed by the other apparatus, and the data processing apparatus may acquire the linkage coefficient between each array element through communication with the other apparatus.

Optionally, the portable relationship determining module may be configured to:

Based on the same principle as the data processing method and apparatus provided in the embodiments of the present application, an embodiment of the present application further provides an electronic device (e.g., a server), where the electronic device may include a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the method provided in any optional embodiment of the present application.

Alternatively, fig. 8 shows a schematic structural diagram of an electronic device to which the embodiment of the present application is applied, and as shown in fig. 8, an electronic device 4000 shown in fig. 8 includes a processor 4001 and a memory 4003. Processor 4001 is coupled to memory 4003, such as via bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, and the transceiver 4004 may be used for data interaction between the electronic device and other electronic devices, such as transmission of data and/or reception of data. In addition, the transceiver 4004 is not limited to one in practical applications, and the structure of the electronic device 4000 is not limited to the embodiment of the present application.

The Processor 4001 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 4001 may also be a combination that performs a computational function, including, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, or the like.

Bus 4002 may include a path that carries information between the aforementioned components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 4002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.

The Memory 4003 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium, other magnetic storage devices, or any other medium that can be used to carry or store a computer program and that can be Read by a computer, without limitation.

The memory 4003 is used for storing computer programs for executing the embodiments of the present application, and is controlled by the processor 4001 to execute. The processor 4001 is used to execute computer programs stored in the memory 4003 to implement the steps shown in the foregoing method embodiments.

Embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, and when being executed by a processor, the computer program may implement the steps and corresponding contents of the foregoing method embodiments.

Embodiments of the present application further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps and corresponding contents of the foregoing method embodiments can be implemented.

It should be understood that, although each operation step is indicated by an arrow in the flowchart of the embodiment of the present application, the implementation order of the steps is not limited to the order indicated by the arrow. In some implementation scenarios of the embodiments of the present application, the implementation steps in the flowcharts may be performed in other sequences as desired, unless explicitly stated otherwise herein. In addition, some or all of the steps in each flowchart may include multiple sub-steps or multiple stages based on an actual implementation scenario. Some or all of these sub-steps or stages may be performed at the same time, or each of these sub-steps or stages may be performed at different times, respectively. In a scenario where execution times are different, an execution sequence of the sub-steps or the phases may be flexibly configured according to requirements, which is not limited in the embodiment of the present application.

The foregoing is only an optional implementation manner of a part of implementation scenarios in this application, and it should be noted that, for those skilled in the art, other similar implementation means based on the technical idea of this application are also within the protection scope of the embodiments of this application without departing from the technical idea of this application.

Claims

1. A method of data processing, the method comprising:

executing at least one optimization operation for each initial lineup in the initial lineup set, determining a target lineup based on the optimized initial lineup set, and for one initial lineup, the optimization operation includes:

determining a first array strength of the initial array;

replacing the array capacity element to be replaced by adopting the new array capacity element, and determining a second array capacity strength of the replaced array capacity;

2. The method according to claim 1, wherein one of the initial lineup comprises at least two types of lineup elements, and each candidate lineup element corresponding to a lineup element to be replaced is a lineup element belonging to the same type as the lineup element to be replaced;

the determining, from each candidate lineup element, a new lineup element corresponding to the lineup element to be replaced based on the linkage coefficient between the lineup element retained in the initial lineup and each candidate lineup element includes:

the first array element is an array element in the reserved array element, which belongs to the same type as the candidate array element, and the second array element is an associated array element of the array element to be replaced, which is not the first array element, in the reserved array element;

and determining a new formation element corresponding to the formation element to be replaced from the candidate formation elements based on the corresponding importance of the candidate formation elements.

3. The method of claim 2, wherein the at least two types of lineup elements comprise two types of lineup elements of virtual roles and virtual skills;

if the lineup element to be replaced is a virtual character, the related lineup element of the virtual character comprises virtual skills of the virtual character;

if the lineup element to be replaced is a virtual skill, the related lineup element of the virtual skill comprises at least one of a target virtual character with the virtual skill or other virtual skills, except the virtual skill, of the target virtual character.

4. The method of claim 1, wherein determining the lineup elements to be replaced in the initial lineup comprises:

and determining the lineup elements to be replaced in the initial lineup from the lineup elements of the initial lineup based on the second importance of the lineup elements in the initial lineup.

5. The method according to any one of claims 1 to 4, wherein one of the initial lineups comprises at least two types of lineup elements, and for one of the initial lineups, each optimization operation takes one type of lineup element in the initial lineup as a lineup element to be replaced, and each type of lineup element in the initial lineup corresponds to at least one optimization operation.

6. The method of any of claims 1 to 4, wherein the initial lineup is a game lineup in a target game application, and wherein the lineup elements in the initial lineup and the candidate lineup elements are lineup elements in the target game application; the carry-together coefficient between the lineup elements in the target game application is determined by:

obtaining attribute information of each lineup element based on the configuration information of each lineup element;

7. The method of claim 6, wherein one lineup element is a virtual character or virtual skill;

for the virtual role, the attribute information of the lineup element comprises at least one item of lineup, role type or trip of the virtual role;

for the virtual skill, the attribute information of the lineup element includes at least one of a skill type, a skill effect, or a skill enhancement condition of the virtual skill.

8. The method according to claim 7, wherein the determining the linkage coefficient between the formation elements according to the matching degree between the attribute information of the formation elements comprises:

9. The method according to any one of claims 1 to 4, further comprising:

the determining the first array capacity strength of the initial array capacity comprises:

10. A data processing apparatus, characterized in that the apparatus comprises:

the system comprises an initial lineup acquisition module, a lineup acquisition module and a lineup analysis module, wherein the initial lineup acquisition module is used for acquiring an initial lineup set, the initial lineup set comprises a plurality of initial lineups, and each initial lineup comprises a plurality of lineup elements;

a target lineup determining module, configured to perform at least one optimization operation on each initial lineup in the initial lineup set, and determine a target lineup based on the optimized initial lineup set, where for an initial lineup, the optimization operation includes:

determining a first array strength of the initial array;

11. An electronic device comprising a memory, a processor and a computer program stored on the memory, characterized in that the processor executes the computer program to implement the steps of the method of any of claims 1-9.

12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 9.

13. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 9 when executed by a processor.