CN111359213A

CN111359213A - Method and apparatus for controlling virtual players in game play

Info

Publication number: CN111359213A
Application number: CN202010212941.7A
Authority: CN
Inventors: 张斌; 王亚昌
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2020-03-24
Filing date: 2020-03-24
Publication date: 2020-07-03
Anticipated expiration: 2040-03-24
Also published as: CN111359213B

Abstract

A method and apparatus for controlling a virtual player in a game pair is described in which a plurality of decision points will occur sequentially in the course of the game pair. The method comprises the following steps: determining mode data of game play; acquiring operation data to be applied by a virtual player in the game play according to the mode data, wherein the operation data comprises an ordered sequence of a plurality of strategy parameter sets which are in one-to-one correspondence with a plurality of decision points appearing in the sequence; controlling the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game play.

Description

Method and apparatus for controlling virtual players in game play

Technical Field

The present disclosure relates to the field of gaming, and in particular to methods and apparatus for controlling virtual players in game plays.

Background

Artificial Intelligence (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. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence. Artificial intelligence is the research of the design principle and the realization method of various intelligent machines, so that the machines have the functions of perception, reasoning and decision making.

As artificial intelligence technology has been researched and developed, artificial intelligence technology has been developed and applied in various fields. For example, in game development and application, artificial intelligence, called game Artificial Intelligence (AI), is used in many scenes. For example, in the game development process, the game AI can replace the role of a tester, and the game AI is introduced to participate in the game to obtain test data so as to realize game performance test. For another example, in the game application process, the game AI can be actively introduced to play with a real person when the number of players is insufficient.

At present, placing games are more and more popular. In a placement type game, a player typically only needs to determine a well-played lineup at the beginning of a game pair, which is then automatically completed according to the game logic and the outcome is output. In current placement-type games, game AI is implemented primarily using a state machine-based scheme, a behavior tree-based scheme, or a machine learning-based scheme. In the scheme based on the state machine, the states in the game AI are mainly organized into a state set, and the next state is determined by condition judgment. This causes many problems such as the representation specification of the game AI, insufficient anthropomorphic degree, easy recognition by other players, and the like. Behavior tree based schemes are essentially an optimization of state machine based schemes and therefore these problems are likewise not avoided. The scheme based on machine learning can alleviate the problems to a certain extent, but a large amount of game data needs to be collected for training and real-time calculation, so a large amount of computer processing resources need to be consumed, and the cost is high; and if the game logic changes during the training process, the game AI can be reflected for a longer time.

Disclosure of Invention

In view of the above, the present disclosure provides methods and apparatus for controlling virtual players in game play, which desirably overcome some or all of the above-referenced deficiencies and possibly others.

According to a first aspect of the present disclosure there is provided a method for controlling a virtual player in a game pair, wherein a plurality of decision points will occur sequentially in the course of the game pair, the method comprising: determining mode data of game play; acquiring operation data to be applied by a virtual player in the game play according to the mode data, wherein the operation data comprises an ordered sequence of a plurality of strategy parameter sets which are in one-to-one correspondence with a plurality of decision points appearing in the sequence; controlling the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game play.

In some embodiments, the mode data includes at least one of a game play mode and a game difficulty level.

In some embodiments, the method further comprises: the game difficulty level is determined according to the level of real players in the game pair.

In some embodiments, the parameters in each of the plurality of policy parameter sets include at least one game character and a state of the at least one game character.

In some embodiments, obtaining operational data to be applied by a virtual player in the game play according to the mode data comprises: historical operation data of the real player corresponding to the mode data is acquired from a set of historical operation data of the real player corresponding to the mode data as operation data to be applied by the virtual player in the game play.

In some embodiments, the course of the game play is managed by a first device, and the course of the game play from which the historical operational data of the real player corresponding to the mode data originates is managed by a second device different from the first device.

In some embodiments, the set of historical operational data of real players corresponding to the mode data comprises a data queue comprising historical operational data of a first predetermined number of real players corresponding to the mode data, wherein obtaining the historical operational data of real players corresponding to the mode data comprises: historical operating data of the real player corresponding to the mode data is obtained from the data queue.

In some embodiments, obtaining historical operational data of the real player corresponding to the mode data from the data queue comprises: acquiring historical operation data of a second preset number of real players from the data queue as buffer data, wherein the second preset number is smaller than or equal to the first preset number; historical operating data of the real player corresponding to the mode data is obtained from the buffer data.

In some embodiments, the method further comprises: and adding the operation data of the real player after the game match is finished as the historical operation data of the real player corresponding to the mode data into the historical operation data set of the real player corresponding to the mode data.

In some embodiments, the method further comprises: adding the operation data of the real player after the game play is finished into a set of the historical operation data of the real player corresponding to the corresponding mode data as the historical operation data of the real player corresponding to the corresponding mode data, wherein the corresponding mode data depends on the mode data of the game play and the game performance ranking of the real player after the game play is finished, and the game performance ranking of the real player represents the fighting performance of the real player in the game play.

In some embodiments, controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises: applying the sets of policy parameters in the ordered sequence in order, one-to-one correspondence with the plurality of sequentially occurring decision points.

In some embodiments, controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises: if it is determined that the game performance ranking of the real player at each of a predetermined number of decision points prior to a current decision point in the game play is lower than the game performance ranking of the virtual player, controlling the virtual player to continue applying the set of strategy parameters applied at a decision point prior to the current decision point at the current decision point, wherein the game performance ranking of the respective one of the real player and the virtual player at each decision point characterizes the engagement performance of the respective player in the game play prior to said each decision point.

In some embodiments, controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises: controlling the virtual player to apply in advance at a current decision point a set of strategy parameters to be applied at a subsequent decision point of a current decision point if it is determined that a game performance ranking of a real player is higher than a game performance ranking of the virtual player at each of a predetermined number of decision points prior to the current decision point in the game pair, wherein the game performance ranking of the respective ones of the real player and the virtual player at each decision point characterizes a competitive performance of the respective player in the game pair prior to the each decision point.

According to a second aspect of the present disclosure there is provided an apparatus for controlling a virtual player in a game pair in which a plurality of decision points will occur sequentially in the course of the game pair, the apparatus comprising: a determination module configured to determine mode data of game play; an acquisition module configured to acquire operation data to be applied by a virtual player in the game play according to the mode data, the operation data including an ordered sequence of a plurality of sets of policy parameters in one-to-one correspondence with the plurality of decision points appearing in the order; a control module configured to control the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game pair.

According to a third aspect of the present disclosure, there is provided a computing device comprising: a memory configured to store computer-executable instructions; a processor configured to perform any of the methods as previously described when the computer-executable instructions are executed by the processor.

According to a fourth aspect of the present disclosure, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed, perform any of the methods as described above.

The method and the device for controlling the virtual player in the game-to-game claimed by the disclosure realize intelligent application of a plurality of strategy parameter sets in the operation data, enhance personification of the game AI, simultaneously basically do not need real-time calculation, save a large amount of processing resources, and compared with a machine learning algorithm using mass data, the required operation data is very light, and save a large amount of machine and memory costs. In addition, the technical scheme of the present disclosure realizes the decoupling with the specific logic of the game, and is beneficial to the transplantation and use among different games. By using the historical operation data of the real player as the operation data applied by the virtual player in the current game-to-game, the fully anthropomorphic game AI can be realized, so that the behavior of the virtual player is real and cannot be recognized by other players, the user experience of the real player is improved, meanwhile, the operation data suitable for the application of the virtual player does not need to be calculated, and a large amount of processing resources are saved.

These and other advantages of the present disclosure will become apparent from and elucidated with reference to the embodiments described hereinafter.

Drawings

Embodiments of the present disclosure will now be described in more detail and with reference to the accompanying drawings, in which:

fig. 1 illustrates an exemplary application scenario in which a technical solution according to an embodiment of the present disclosure may be implemented;

FIG. 2 illustrates a schematic flow diagram of a method for controlling a virtual player in a game pair according to one embodiment of the present disclosure;

FIG. 3 illustrates a schematic flow chart diagram of a method for controlling a virtual player in a game pair in accordance with another embodiment of the present disclosure;

FIG. 4 illustrates a schematic flow chart diagram of a method for controlling a virtual player in a game pair in accordance with another embodiment of the present disclosure;

FIG. 5 is an exemplary user interface illustrating a set of policy parameters according to one embodiment of the present disclosure;

FIG. 6 illustrates a schematic diagram of a correspondence of mode data for a game play to a set of historical operational data of a real player, according to one embodiment of the present disclosure;

FIG. 7 illustrates a schematic diagram of a data queue of historical operational data of real players corresponding to mode data in one embodiment in accordance with the present disclosure;

FIG. 8 illustrates an exemplary scenario in which a data queue is held independently according to one embodiment of the present disclosure;

FIG. 9 illustrates an exemplary user interface for controlling a virtual player to apply a set of policy parameters according to one embodiment of the present disclosure;

FIG. 10 illustrates an exemplary block diagram of an apparatus for controlling a virtual player in a game pair according to one embodiment of the present disclosure; and

fig. 11 illustrates an example system that includes an example computing device that represents one or more systems and/or devices that may implement the various techniques described herein.

Detailed Description

The following description provides specific details for a thorough understanding and enabling description of various embodiments of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these details. In some instances, well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments of the disclosure. The terminology used in the present disclosure is to be understood in its broadest reasonable manner, even though it is being used in conjunction with a particular embodiment of the present disclosure.

First, some terms referred to in the embodiments of the present application are explained so that those skilled in the art can understand that:

AI is an abbreviation for Artificial Intelligence, Chinese translates to Artificial Intelligence, used herein to refer specifically to simulating and fighting a player in a game;

placing a game: the game type is a game type which can automatically run according to a series of operation rules of the system and obtain a game result only by determining a strategy when a player starts game match, such as a popular 'many-go' game at present.

Fig. 1 illustrates an exemplary application scenario 100 in which a technical solution according to an embodiment of the present disclosure may be implemented. As shown in fig. 1, the application scenario 100 includes a terminal 101 and a server 102, and the terminal 101 is communicatively coupled with the server 102 through a network 103. A game client 104 may be run on the terminal 101, and the game client 104 may display a game including a virtual game character manipulated by a player, such as the placement-type game described above. The server 102 may be, for example, a game server or a cluster of game servers having functionality to manage the progress of game-play of the game and to process game logic. When the number of players is insufficient in the automatic running, testing or one game of the game, the game AI can be actively introduced to play the game, namely, a virtual player is created to play the game with a real player. Control of the virtual player may be hosted to server 102, for example. A method for controlling a virtual player in a game pair according to embodiments of the present disclosure may be run on the server 102 to enable control of the virtual player. By way of example, server 102 may determine pattern data for a game pair in which a plurality of decision points will occur sequentially; then, acquiring operation data to be applied by a virtual player in the game play according to the mode data, wherein the operation data comprises an ordered sequence of a plurality of strategy parameter sets which are in one-to-one correspondence with a plurality of decision points appearing in the sequence; finally, at the plurality of decision points that occur sequentially in a game pair, controlling the virtual player to apply the sets of strategy parameters in the ordered sequence in sequence, thereby implementing game AI in the game pair. It should be noted that the method for controlling a virtual player in a game pair according to an embodiment of the present disclosure may be implemented not only on the server 102, but also on the client 101 or any other possible entity, which is not limiting.

Optionally, the terminal 101 may include, but is not limited to, at least one of the following: the mobile phone, the tablet computer, the notebook computer, the desktop computer, the digital television and the like can run the terminal of the game client. The server 102 may include, but is not limited to, at least one of: mainframe, minicomputer, microcomputer, and other various computing devices for game control. The network 103 may be, for example, a Wide Area Network (WAN), a Local Area Network (LAN), a wireless network, a public telephone network, an intranet, or any other type of network known to those skilled in the art. It should be noted that the scenario described above is only one example in which the embodiments of the present disclosure may be implemented, and is not limiting.

FIG. 2 illustrates a schematic flow diagram of a method 200 for controlling virtual players in a game pair according to one embodiment of the present disclosure, which is generally applied in a game server, such as the server 102 described with reference to FIG. 1, having the functions of managing the progress of the game pair and processing game logic, although this is not limiting. A plurality of decision points will appear sequentially in the course of the game play. The decision point represents a certain time point or a certain time period in which a player needs to input instructions or commands in the game process, and after the player inputs corresponding instructions or commands at the decision point, the game can automatically run for the game without the intervention of the player. As shown in fig. 2, the method 200 includes the following steps.

In step 201, mode data for game play is determined. In some embodiments, the mode data includes at least one of a game play mode and a game difficulty level. The game match mode refers to, for example, a 1-person-to-1-person match mode (1 vs 1), a four-person-to-four-person grouping match mode (4 vs 4), a hybrid match mode for each player, and the like. Generally, to enhance the game experience, the game may set different game difficulty levels for different levels of players to participate in the game. By way of example, the game difficulty level may refer to the difficulty of a game versus a game, such as a primary, a secondary, a high level, and the like. As another example, the game difficulty level may also be determined based on the level of real players in the game versus. For example, the average level of the levels of real players in a game pair may be determined as the difficulty level of the game pair. For example, if there are currently two high-level real players, four middle-level real players, and one low-level real player in a game pair, the game difficulty level of the game pair may be determined as a middle level.

In step 202, operation data to be applied by the virtual player in the game play is acquired according to the mode data, wherein the operation data comprises an ordered sequence of a plurality of strategy parameter sets in one-to-one correspondence with a plurality of decision points appearing in the sequence. By acquiring operation data to be applied by a virtual player in the game play according to the mode data, operation data matching the mode data can be acquired, such operation data being suitable for application by a virtual player in the game play. The acquired operation data is matched with the fighting mode of the game match, so that the behavior of the virtual player can be prevented from being separated from the game mode, and the personification of the game AI is enhanced. The obtained operation data is matched with the game difficulty level of the game match, so that the excessive difference of the game levels of the real player and the virtual player can be avoided, and the user experience of the real player is improved.

In some embodiments, the parameters in each of the plurality of policy parameter sets include at least one game character and a state of the at least one game character. Of course this is not limiting and the set of policy parameters may also include other further parameters such as the player's economy, candidate game characters operable by the player, and so on. The player's economy may be used to upgrade the equipment of the game character, purchasing operational candidate game characters. A player may select a game character from the actionable candidate game characters for application at a decision point to engage with other player's game characters in a battle field. The at least one game character represents a virtual game character that a player plays in a game, and the win or loss of the player or the game performance score is decided by the match between the virtual game characters of different players in one game. The state of the game character represents the position of the game character in the game, the amount of combat power it has (which is typically reflected by the equipment or level of the virtual game character in the game), and so on.

As an example, fig. 5 is an exemplary user interface showing one set of strategy parameters according to one embodiment of the present disclosure, and in particular, fig. 5 shows the set of strategy parameters applied at a decision point in a game play before the start of a 10 th round of play. The parameters in the set of policy parameters include two game characters "taijizongzo", "muggy superman", and states of the two game characters, wherein the game character "taijizongzo" is ranked 2 and stands at a position on the upper left of the battle field, and the game character "muggy superman" is ranked 3 and stands at a position on the lower middle of the battle field. Also shown in fig. 5 are other parameters that may optionally be included in the set of policy parameters, such as a player operable level 1 candidate game character "win" and a level 1 candidate game character "wizard".

In some embodiments, when acquiring the operation data to be applied by the virtual player in the game play according to the mode data, the historical operation data of the real player may be acquired from a set of historical operation data of the real player corresponding to the mode data as the operation data to be applied by the virtual player in the game play. The historical operation data of the real player corresponding to the mode data is used as the operation data applied by the virtual player in the game play, so that the complete personification of the game AI can be realized, the behavior of the virtual player is real, the virtual player can not be identified by other players, meanwhile, the operation data suitable for the application of the virtual player does not need to be calculated, and a large amount of processing resources are saved.

The set of historical operational data of real players corresponding to the mode data may be predetermined, for example, a large number of historical operational data of real players may be obtained and sorted by different mode data to form different sets of historical operational data of real players corresponding to different mode data. That is, the mode data is used as an index of the historical operation data of the real player. FIG. 6 illustrates a schematic diagram of a correspondence of mode data of game play-pairs to a set of historical operational data of real players, according to one embodiment of the present disclosure. As shown in FIG. 6, the first mode data corresponds to a first set of historical operational data of a real player, the second mode data corresponds to a second set of historical operational data of the real player, and the third mode data corresponds to a third set of historical operational data of the real player, wherein each mode data includes a game play mode and a game difficulty level. The first mode data is, for example, a game play mode of 4vs4 and a game difficulty level of a primary difficulty level, the second mode data is, for example, a game play mode of 4vs4 and a game difficulty level of a middle difficulty level, and the third mode data is, for example, a game play mode of 4vs4 and a game difficulty level of a high difficulty level. In other words, the game match pattern and the game difficulty level constitute an index word pair of a set of the historical operation data of the real player.

In some embodiments, if the progress of the game play is managed by a first device (e.g., one of a cluster of game servers), in obtaining operational data to be applied by the virtual player in said game pair, it is advantageous to obtain historical operational data of real players originating from such further game pairs, the progress of the further game play is managed by a second device, different from the first device, e.g. another server in the game server cluster, this can ensure that the dispersion of the acquired operation data is relatively high, prevent the game-play managed on one device (or server) from applying the operation data from the game-play managed on the same device (or server), the likelihood that the player finds the process of game play (i.e., the set of strategy parameters applied by the virtual player) like a great acquaintance can thereby be avoided or reduced.

In some embodiments, the set of historical operational data of real players corresponding to the mode data is in the form of a data queue, which may include historical operational data of a first predetermined number of real players corresponding to the mode data. In this case, when the historical operation data of the real player corresponding to the mode data is acquired, the historical operation data of the real player corresponding to the mode data may be acquired from the data queue. A data queue is a data structure that has a first-in-first-out feature, i.e., the data queue allows data to be inserted only at one end and data to be removed or deleted at the other end, so that only the earliest data entering the data queue can be removed or deleted from the data queue first. The data queue typically has a fixed capacity (e.g., the first predetermined amount described above), and if the operation data in the data queue reaches the fixed capacity, the operation data that was entered into the data queue earliest will be discarded as new operation data arrives. Because the accumulation speed of the historical operation data is high, the data queue is provided with the first preset amount of historical operation data, so that the amount of the historical operation data can be controlled, the unlimited consumption of storage resources is avoided, and meanwhile, the old and new data can be continuously updated, and the oldest operation data is replaced by the newest operation data. Even if the game logic is changed, the operation data can be updated rapidly, the efficiency and effect of the game AI are greatly improved, and the processing resource for updating the operation data is saved.

FIG. 7 illustrates a schematic diagram of a data queue of historical operational data of real players corresponding to mode data in one embodiment according to the present disclosure. FIG. 7 illustrates three data queues, a first data queue including historical operational data of a real player corresponding to first mode data, a second data queue including historical operational data of a real player corresponding to second mode data, and a third data queue including historical operational data of a real player corresponding to third mode data. The first mode data is, for example, a match mode of 4vs4 and a game difficulty level of a primary difficulty, the second mode data is, for example, a match mode of 4vs4 and a game difficulty level of a middle difficulty, and the third mode data is, for example, a match mode of 4vs4 and a game difficulty level of a high difficulty. As shown in fig. 7, each data queue allows only insertion of operation data at its left end and extraction or deletion of operation data at its right end.

As an example, the amount of operational data in the data queue is also undesirably small, typically because the number of game players and game plays is quite large, and thus the data queue may need to be stored separately on a dedicated storage device, which may be local or remote with respect to the game server. Accordingly, in some embodiments, historical operation data of a second predetermined number of real players may be obtained from the data queue as buffered data, and then historical operation data of real players corresponding to the mode data may be obtained from the buffered data, where the second predetermined number is less than or equal to the first predetermined number. The buffer data can be stored locally or in the memory of the device (e.g., game server) applying the operation data, which can speed up the acquisition of the operation data, thereby improving the efficiency and effect of the game AI. Fig. 8 shows an illustrative scenario in which a data queue is maintained separately, wherein the data queue is maintained separately on a storage server, according to one embodiment of the present disclosure. As an example, the game server may request, from the storage server, the historical operation data of a second predetermined number of real players to be saved as buffer data in a local storage or a memory of the game server, and the game server may store, as the historical operation data, the operation data of the real players after the end of the game play as the historical operation data in a data queue saved by the storage server, in order to, for example, eliminate and update old data therein. In some embodiments, to support storage server restart and expansion followed by initial data, all data queues on the storage server may be backed up periodically to the backup server.

At step 203, controlling the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points sequentially appearing in the game play. The virtual players are controlled to sequentially apply the strategy parameter sets in the ordered sequence at the decision points in the game, so that the smooth progress of the game is ensured, the highly anthropomorphic game AI is realized, the corresponding strategy parameter sets do not need to be calculated at each decision point in real time according to the game result or scene, and a large amount of processing resources are saved.

In some embodiments, the sets of policy parameters in the ordered sequence may be applied sequentially, in one-to-one correspondence with the plurality of sequentially occurring decision points. For example, where the operational data includes a first set of policy parameters at a first decision point, a second set of policy parameters at a second decision point, a third set of policy parameters at a third decision point, a fourth set of policy parameters at a fourth decision point, a fifth set of policy parameters at a fifth decision point, the first set of policy parameters may be applied at the first decision point, the second set of policy parameters may be applied at the second decision point, and so on, occurring in a game pair.

In some embodiments, if it is determined that the game performance ranking of the real player at each of a predetermined number of decision points prior to the current decision point in the game pair is lower than the game performance ranking of the virtual player, controlling the virtual player to continue applying the set of policy parameters applied at the decision point immediately preceding the current decision point at the current decision point. The game performance ranking of the respective ones of the real and virtual players at each decision point characterizes the competitive performance of the respective player in the game play before the each decision point. The higher the game performance ranking of the player, the better the competitive performance in the game play. The game performance ranking may generally be determined by the number of credits earned, the number of times the opponent's game character is defeated, the number of extermination of the opponent's game character, and so forth. After the game play is over, the player whose game performance ranking is the first or first few is typically determined to be the winner in the game play. As an example, taking the five decision points described above as an example, if the current decision point in the game pair is the fourth decision point, and the game performance ranks of the real players at the second decision point and the third decision point are both lower than the game performance ranks of the virtual players (here, the predetermined number is 2), the third policy parameter set applied at the previous decision point (i.e., the third policy parameter set) is continuously applied at the current fourth decision point, while the fourth policy parameter set is delayed from being applied.

In some embodiments, if it is determined that the game performance ranking of the real player is higher than the game performance ranking of the virtual player at each of a predetermined number of decision points before the current decision point in the game pair, controlling the virtual player to apply in advance at the current decision point the set of policy parameters to be applied at a subsequent decision point to the current decision point. As an example, taking the five decision points described above as an example, if the current decision point in the game pair is the fourth decision point, and the game performance ranks of the real players are higher than the game performance ranks of the virtual players at both the second decision point and the third decision point (here, the predetermined number is 2), the policy parameter group to be applied at the next decision point (i.e., the fifth decision point) (i.e., the fifth policy parameter group) is applied in advance at the current fourth decision point, and the fourth policy parameter group is skipped (i.e., not applied) in the game pair.

By the method for controlling the virtual player in the game-to-game, intelligent application of a plurality of strategy parameter sets in the operation data is realized, personification of the game AI is enhanced, meanwhile, real-time calculation is basically not needed, a large amount of processing resources are saved, and compared with a machine learning algorithm using mass data, the required operation data is very light, and a large amount of machine and memory costs are saved. Furthermore, as can be seen from the above, the implementation of the method is decoupled from the specific logic of the game, which facilitates its use in a mobile inter-game environment.

Fig. 3 illustrates a schematic flow diagram of a method 300 for controlling virtual players in game pairings according to another embodiment of the present disclosure, which is generally applied in a game server, such as the server 102 described with reference to fig. 1, having the functions of managing the progress of game pairings and processing game logic, although this is not limiting. The method 300 comprises the steps 301-. It should be noted, however, that in step 302 of method 300, historical operational data of the real player corresponding to the mode data is obtained from a set of historical operational data of the real player corresponding to the mode data as operational data to be applied by the virtual player in the game play, as described above.

In step 304, the operation data of the real player after the game play is finished is added as the historical operation data of the real player corresponding to the mode data to the set of the historical operation data of the real player corresponding to the mode data. As an example, if the mode data of the game play is the first mode data, the operation data of all real players in the game play is added as the historical operation data corresponding to the first mode data to the set of the historical operation data of the real players corresponding to the first mode data. This provides a simple and efficient way of obtaining operational data, saves a lot of computing and processing resources needed for computing and obtaining operational data, and even if the game logic changes, the operational data can be reflected very quickly, the behavior of the virtual player is thereby updated, and the update speed and the personification effect of the game AI are greatly improved.

Fig. 4 illustrates a schematic flow diagram of a method 400 for controlling virtual players in a game pair according to another embodiment of the present disclosure, which is generally applied in a game server, such as the server 102 described with reference to fig. 1, having functions of managing the progress of the game pair and processing game logic, although this is not limiting. The method 400 comprises steps 401-. It should be noted, however, that in step 402 of method 400, historical operational data of the real player corresponding to the mode data is obtained from a set of historical operational data of the real player corresponding to the mode data as operational data to be applied by the virtual player in the game play, as described above.

In step 404, the operation data of the real player after the game play is finished is added as the historical operation data of the real player corresponding to the corresponding mode data to the set of the historical operation data of the real player corresponding to the corresponding mode data. The respective mode data is dependent on mode data of the game play and a game performance ranking of the real player after the game play is ended, the game performance ranking of the real player characterizing a play performance of the real player in the game play.

As an example, if the mode data of the game play is the first mode data, such as the play mode of 4vs4 and the game difficulty level of the primary difficulty, the operation data of the real player whose game representation in the game play is ranked 1-3 is added as the historical operation data corresponding to the third mode data (e.g., the play mode of 4vs4 and the game difficulty level of the advanced difficulty) to the set of the historical operation data of the real player corresponding to the third mode data; adding operation data of a real player ranked 4-6 in game performance in the game play as historical operation data corresponding to second mode data (e.g., a match mode of 4vs4 and a game difficulty level of a middle difficulty level) to a set of historical operation data of the real player corresponding to the second mode data; the operation data of the real player ranked 7-8 in the game performance in the game play is added as the historical operation data corresponding to the first mode data (for example, the play mode of 4vs4 and the game difficulty level of the primary difficulty) to the set of the historical operation data of the real player corresponding to the first mode data. The method for simply and efficiently constructing the set of the historical operation data of the real player corresponding to the different mode data of the game match provides a large amount of calculation and processing resources, and greatly improves the efficiency and the effect of the game AI.

FIG. 9 illustrates an exemplary user interface for controlling a virtual player to apply a set of policy parameters according to one embodiment of the present disclosure. In fig. 9, the virtual player applied the sets of play parameters shown in fig. 5, and it can be seen that in the 10 th round of the game play, the game character played by the virtual player automatically plays a match with the game characters played by other players in the match area to win or lose the win or to obtain the respective game performance scores.

FIG. 10 illustrates an exemplary block diagram of an apparatus 1000 for controlling a virtual player in a game pair according to one embodiment of the present disclosure. As shown in fig. 10, the apparatus 1000 includes a determination module 1001, an acquisition module 1002, and a control module 1003. In some embodiments, the apparatus 1000 may optionally further include a data join module 1004.

The determination module 1001 is configured to determine mode data for game play. A plurality of decision points will appear sequentially in the course of the game play. In some embodiments, the mode data includes at least one of a game play mode and a game difficulty level. The game match mode refers to, for example, a 1-person-to-1-person match mode (1 vs 1), a four-person-to-four-person grouping match mode (4 vs 4), an individual-player mixed match mode, and the like.

The obtaining module 1002 is configured to obtain operation data to be applied by the virtual player in the game play according to the mode data, the operation data including an ordered sequence of a plurality of policy parameter sets in one-to-one correspondence with the plurality of sequentially occurring decision points. In some embodiments, the parameters in each of the plurality of policy parameter sets include at least one game character and a state of the at least one game character.

In some embodiments, the obtaining module 1002 may be configured to obtain historical operation data of the real player from a set of historical operation data of the real player corresponding to the mode data as operation data to be applied by the virtual player in the game play. In some embodiments, the set of historical operational data of the real player corresponding to the mode data comprises a data queue comprising historical operational data of a first predetermined number of real players corresponding to the mode data, and the obtaining module 1002 may be configured to obtain the historical operational data of the real player corresponding to the mode data from the data queue. In some embodiments, the obtaining module 1002 may be configured to obtain, as the buffer data, historical operation data of a second predetermined number of real players from the data queue, and then obtain, from the buffer data, historical operation data of real players corresponding to the mode data, where the second predetermined number is less than or equal to the first predetermined number.

The control module 1003 is configured to control the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game pair. In some embodiments, the control module 1003 is configured to apply the sets of policy parameters in the ordered sequence in order, in one-to-one correspondence with the plurality of sequentially occurring decision points. In some embodiments, the control module is configured to: if it is determined that the game performance ranking of the real player at each of a predetermined number of decision points prior to a current decision point in the game play is lower than the game performance ranking of the virtual player, controlling the virtual player to continue applying the set of strategy parameters applied at a decision point prior to the current decision point at the current decision point, wherein the game performance ranking of the respective one of the real player and the virtual player at each decision point characterizes the engagement performance of the respective player in the game play prior to said each decision point. In some embodiments, the control module is configured to: controlling the virtual player to apply in advance at a current decision point a set of strategy parameters to be applied at a subsequent decision point of a current decision point if it is determined that a game performance ranking of a real player is higher than a game performance ranking of the virtual player at each of a predetermined number of decision points prior to the current decision point in the game pair, wherein the game performance ranking of the respective ones of the real player and the virtual player at each decision point characterizes a competitive performance of the respective player in the game pair prior to the each decision point.

In a case where the acquiring module 1002 is configured to acquire the historical operation data of the real player from the set of the historical operation data of the real player corresponding to the mode data as the operation data to be applied by the virtual player in the game play, the data adding module 1004 is configured to add the operation data of the real player after the game play ends as the historical operation data of the real player corresponding to the mode data to the set of the historical operation data of the real player corresponding to the mode data. In some embodiments, the data adding module 1004 is configured to add the operation data of the real player after the game play is ended as historical operation data of the real player corresponding to the corresponding mode data to the set of historical operation data of the real player corresponding to the corresponding mode data, wherein the corresponding mode data depends on the mode data of the game play and the game performance ranking of the real player after the game play is ended, and the game performance ranking of the real player characterizes the engagement performance of the real player in the game play.

Fig. 11 illustrates an example system 1100 that includes an example computing device 1110 that represents one or more systems and/or devices that can implement the various techniques described herein. Computing device 1110 may be, for example, a server of a service provider, a device associated with a server, a system on a chip, and/or any other suitable computing device or computing system. The device 1000 for controlling virtual players in a game pair described above with respect to fig. 10 may take the form of a computing device 1110. Alternatively, the device 1000 for controlling a virtual player in a game pair may be implemented as a computer program in the form of a virtual player control application 1116.

The example computing device 1110 as illustrated includes a processing system 1111, one or more computer-readable media 1112, and one or more I/O interfaces 1113 communicatively coupled to each other. Although not shown, the computing device 1110 may also include a system bus or other data and command transfer system that couples the various components to one another. A system bus can include any one or combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and/or a processor or local bus that utilizes any of a variety of bus architectures. Various other examples are also contemplated, such as control and data lines.

Processing system 1111 represents functionality to perform one or more operations using hardware. Thus, the processing system 1111 is illustrated as including hardware elements 1114 that can be configured as processors, functional blocks, and the like. This may include implementation in hardware as an application specific integrated circuit or other logic device formed using one or more semiconductors. Hardware elements 1114 are not limited by the materials from which they are formed or the processing mechanisms employed therein. For example, a processor may be comprised of semiconductor(s) and/or transistors (e.g., electronic Integrated Circuits (ICs)). In such a context, processor-executable instructions may be electronically-executable instructions.

Computer-readable medium 1112 is illustrated as including memory/storage 1115. Memory/storage 1115 represents memory/storage capacity associated with one or more computer-readable media. The memory/storage 1115 may include volatile media (such as Random Access Memory (RAM)) and/or nonvolatile media (such as Read Only Memory (ROM), flash memory, optical disks, magnetic disks, and so forth). Memory/storage 1115 may include fixed media (e.g., RAM, ROM, a fixed hard drive, etc.) as well as removable media (e.g., flash memory, a removable hard drive, an optical disk, and so forth). Computer-readable medium 1112 may be configured in various other ways as further described below.

One or more I/O interfaces 1113 represent functionality to allow a user to enter commands and information to computing device 1110 and optionally also to present information to the user and/or other components or devices using various input/output devices. Examples of input devices include a keyboard, a cursor control device (e.g., a mouse), a microphone (e.g., for voice input), a scanner, touch functionality (e.g., capacitive or other sensors configured to detect physical touch), a camera (e.g., motion that may not involve touch may be detected as gestures using visible or invisible wavelengths such as infrared frequencies), and so forth. Examples of output devices include a display device (e.g., a monitor or projector), speakers, a printer, a network card, a haptic response device, and so forth. Thus, the computing device 1110 may be configured in various ways as further described below to support user interaction.

Computing device 1110 also includes a virtual player control application 1116. The virtual player control application 1116 may be, for example, a software instance of device 1000 for controlling a virtual player in a game play and implement the techniques described herein in combination with other elements in computing device 1110.

Various techniques may be described herein in the general context of software hardware elements or program modules. Generally, these modules include routines, programs, objects, elements, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The terms "module," "functionality," and "component" as used herein generally represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, meaning that the techniques may be implemented on a variety of computing platforms having a variety of processors.

An implementation of the described modules and techniques may be stored on or transmitted across some form of computer readable media. Computer readable media can include a variety of media that can be accessed by computing device 1110. By way of example, and not limitation, computer-readable media may comprise "computer-readable storage media" and "computer-readable signal media".

"computer-readable storage medium" refers to a medium and/or device, and/or a tangible storage apparatus, capable of persistently storing information, as opposed to mere signal transmission, carrier wave, or signal per se. Accordingly, computer-readable storage media refers to non-signal bearing media. Computer-readable storage media include hardware such as volatile and nonvolatile, removable and non-removable media and/or storage devices implemented in a method or technology suitable for storage of information such as computer-readable instructions, data structures, program modules, logic elements/circuits or other data. Examples of computer readable storage media may include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical storage, hard disks, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or other storage devices, tangible media, or an article of manufacture suitable for storing the desired information and accessible by a computer.

"computer-readable signal medium" refers to a signal-bearing medium configured to transmit instructions to the hardware of computing device 1110, such as via a network. Signal media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave, data signal or other transport mechanism. Signal media also includes any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

As previously described, the hardware elements 1114 and the computer-readable media 1112 represent instructions, modules, programmable device logic, and/or fixed device logic implemented in hardware form that may be used in some embodiments to implement at least some aspects of the techniques described herein. The hardware elements may include integrated circuits or systems-on-chips, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), Complex Programmable Logic Devices (CPLDs), and other implementations in silicon or components of other hardware devices. In this context, a hardware element may serve as a processing device that performs program tasks defined by instructions, modules, and/or logic embodied by the hardware element, as well as a hardware device for storing instructions for execution, such as the computer-readable storage medium described previously.

Combinations of the foregoing may also be used to implement the various techniques and modules described herein. Thus, software, hardware, or program modules and other program modules may be implemented as one or more instructions and/or logic embodied on some form of computer-readable storage medium and/or by one or more hardware elements 1114. The computing device 1110 may be configured to implement particular instructions and/or functions corresponding to software and/or hardware modules. Thus, implementing modules as modules executable by the computing device 1110 as software may be implemented at least partially in hardware, for example, using the processing system's computer-readable storage media and/or hardware elements 1114. The instructions and/or functions may be executable/operable by one or more articles of manufacture (e.g., one or more computing devices 1110 and/or processing systems 1011) to implement the techniques, modules, and examples described herein.

In various embodiments, computing device 1110 may assume a variety of different configurations. For example, the computing device 1110 may be implemented as a computer-like device including a personal computer, a desktop computer, a multi-screen computer, a laptop computer, a netbook, and so forth. The computing device 1110 may also be implemented as a mobile device-like device including mobile devices such as mobile telephones, portable music players, portable gaming devices, tablet computers, multi-screen computers, and the like. Computing device 1110 may also be implemented as a television-like device that includes devices with or connected to generally larger screens in casual viewing environments. These devices include televisions, set-top boxes, game consoles, and the like.

The techniques described herein may be supported by these various configurations of computing device 1110 and are not limited to specific examples of the techniques described herein. Functionality may also be implemented in whole or in part on "cloud" 1120 using a distributed system, such as through platform 1122 described below.

Cloud 1120 includes and/or is representative of platform 1122 for resources 1124. Platform 1122 abstracts underlying functionality of hardware (e.g., servers) and software resources of cloud 1120. Resources 1124 can include applications and/or data that can be used when executing computer processes on servers remote from computing device 1110. Resources 1124 may also include services provided over the internet and/or over a subscriber network such as a cellular or Wi-Fi network.

The platform 1122 may abstract resources and functionality to connect the computing device 1110 with other computing devices. The platform 1122 may also be used to abstract a hierarchy of resources to provide a corresponding level of hierarchy of encountered demand for the resources 1124 implemented via the platform 1122. Thus, in interconnected device embodiments, implementation of functions described herein may be distributed throughout the system 1100. For example, the functionality may be implemented in part on the computing device 1110 and by the platform 1122 that abstracts the functionality of the cloud 1120.

It will be appreciated that embodiments of the disclosure have been described with reference to different functional units for clarity. However, it will be apparent that the functionality of each functional unit may be implemented in a single unit, in a plurality of units or as part of other functional units without departing from the disclosure. For example, functionality illustrated to be performed by a single unit may be performed by a plurality of different units. Thus, references to specific functional units are only to be seen as references to suitable units for providing the described functionality rather than indicative of a strict logical or physical structure or organization. Thus, the present disclosure may be implemented in a single unit or may be physically and functionally distributed between different units and circuits.

It will be understood that, although the terms first, second, third, etc. may be used herein to describe various devices, elements, components or sections, these devices, elements, components or sections should not be limited by these terms. These terms are only used to distinguish one device, element, component or section from another device, element, component or section.

Although the present disclosure has been described in connection with some embodiments, it is not intended to be limited to the specific form set forth herein. Rather, the scope of the present disclosure is limited only by the accompanying claims. Additionally, although individual features may be included in different claims, these may possibly advantageously be combined, and the inclusion in different claims does not imply that a combination of features is not feasible and/or advantageous. The order of features in the claims does not imply any specific order in which the features must be worked. Furthermore, in the claims, the word "comprising" does not exclude other elements, and the terms "a" or "an" do not exclude a plurality. Reference signs in the claims are provided merely as a clarifying example and shall not be construed as limiting the scope of the claims in any way.

Claims

1. A method for controlling a virtual player in a game pair, wherein a plurality of decision points will occur sequentially in the course of the game pair, the method comprising:

determining mode data of game play;

acquiring operation data to be applied by a virtual player in the game play according to the mode data, wherein the operation data comprises an ordered sequence of a plurality of strategy parameter sets which are in one-to-one correspondence with a plurality of decision points appearing in the sequence;

controlling the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game play.

2. The method of claim 1, wherein the mode data includes at least one of a game play mode and a game difficulty level.

3. The method of claim 2, further comprising:

the game difficulty level is determined according to the level of real players in the game pair.

4. The method of claim 1, wherein the parameters in each of the plurality of sets of policy parameters include at least one game character and a state of the at least one game character.

5. The method of any of claims 1 to 4, wherein obtaining operational data to be applied by a virtual player in the game play according to the mode data comprises:

historical operation data of the real player corresponding to the mode data is acquired from a set of historical operation data of the real player corresponding to the mode data as operation data to be applied by the virtual player in the game play.

6. The method of claim 5, wherein the set of historical operational data of the real player corresponding to the mode data comprises a data queue including historical operational data of a first predetermined number of real players corresponding to the mode data, wherein obtaining the historical operational data of the real player corresponding to the mode data comprises:

historical operating data of the real player corresponding to the mode data is obtained from the data queue.

7. The method of claim 6, wherein obtaining historical operational data of the real player corresponding to the mode data from the data queue comprises:

acquiring historical operation data of a second preset number of real players from the data queue as buffer data, wherein the second preset number is smaller than or equal to the first preset number;

historical operating data of the real player corresponding to the mode data is obtained from the buffer data.

8. The method of claim 5, further comprising:

and adding the operation data of the real player after the game match is finished as the historical operation data of the real player corresponding to the mode data into the historical operation data set of the real player corresponding to the mode data.

9. The method of claim 5, further comprising:

adding the operation data of the real player after the game-play is finished as the historical operation data of the real player corresponding to the corresponding mode data into the historical operation data set of the real player corresponding to the corresponding mode data,

wherein the respective mode data is dependent on mode data of the game play and a game performance ranking of the real player after the game play ends, the game performance ranking of the real player characterizing a play performance of the real player in the game play.

10. The method of claim 1, wherein controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises:

applying the sets of policy parameters in the ordered sequence in order, one-to-one correspondence with the plurality of sequentially occurring decision points.

11. The method of claim 1, wherein controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises:

if it is determined that the game performance ranking of the real player at each of a predetermined number of decision points prior to a current decision point in the game play is lower than the game performance ranking of the virtual player, controlling the virtual player to continue applying the set of strategy parameters applied at a decision point prior to the current decision point at the current decision point, wherein the game performance ranking of the respective one of the real player and the virtual player at each decision point characterizes the engagement performance of the respective player in the game play prior to said each decision point.

12. The method of claim 1, wherein controlling the virtual player to sequentially apply the sets of policy parameters in the ordered sequence comprises:

controlling the virtual player to apply in advance at a current decision point a set of strategy parameters to be applied at a subsequent decision point of a current decision point if it is determined that a game performance ranking of a real player is higher than a game performance ranking of the virtual player at each of a predetermined number of decision points prior to the current decision point in the game pair, wherein the game performance ranking of the respective ones of the real player and the virtual player at each decision point characterizes a competitive performance of the respective player in the game pair prior to the each decision point.

13. An apparatus for controlling a virtual player in a game pair, wherein a plurality of decision points will occur sequentially in the course of the game pair, the apparatus comprising:

a determination module configured to determine mode data of game play;

an acquisition module configured to acquire operation data to be applied by a virtual player in the game play according to the mode data, the operation data including an ordered sequence of a plurality of sets of policy parameters in one-to-one correspondence with the plurality of decision points appearing in the order;

a control module configured to control the virtual player to sequentially apply the sets of strategy parameters in the ordered sequence at the plurality of decision points that occur sequentially in a game pair.

14. A computing device, comprising:

a memory configured to store computer-executable instructions;

a processor configured to perform the method of any one of claims 1-12 when the computer-executable instructions are executed by the processor.

15. A computer-readable storage medium storing computer-executable instructions that, when executed, perform the method of any one of claims 1-12.