CN105893656A - Platform-level Agent interactive simulation-oriented army unit combat test method - Google Patents

Abstract

The invention relates to a platform-level Agent interactive simulation-oriented army unit combat test method. The method comprises flow design of a platform-level Agent interactive simulation-oriented combat test, a design method of the platform-level Agent interactive simulation-oriented combat test, a development method of platform-level Agent interactive simulation-oriented army unit combat test. According to the method, in allusion to the complex adaptive system characteristics of the modern army combat, the basic flows of the army unit combat test is designed and the realization method of the main test flow links such as test design and test development is designed by adopting a platform-level multi-Agent-based combat modeling and simulation technology, so that theory and method supports are provided for the high-resolution army unit combat test.

Description

A kind of unit of ground force operational experiments method of object platform level Agent interactive simulation

[technical field]

The present invention relates to a kind of operational experiments method, be specifically related to the ground force of a kind of object platform level Agent interactive simulation Unit's operational experiments method, belongs to Computer Warfare Simulation technical field.

[background technology]

Along with the arrival of information age, various new and high technologies apply to battlefield so that battlefield complexity is greatly improved." from War learning war ", it is by theory of wars research and tactics checks effective method, but in the current peace epoch, The war not adapted with Weapon Development is available for our Learning Studies, also need not be with this to destroy the side as cost Formula studies war, then replaces the method operational experiments of war with experiment, is developed rapidly.

U.S. army successively proposes the most close concept in terms of operational experiments, reflects the process of cognition to operational experiments.Bag Include national defence experiment, military experiment, operational experiments, and joint warfighting experiment etc..In China, famous scientist's Qian Xuesen is then Being initiator, as far back as 1979, Qian Xuesen was just pointed out: " under the conditions of the controllable operation of simulation, carry out operational experiments, Complex relationship between can using relevant Forces And Weapons equipment obtains quantitative deep understanding.Operational experiments, is army The epoch-making innovation of thing scientific research methods." operational experiments thought propose after, go through the exploration of decades, the work of China War experiment is gradually entered into practice by theory study, and the Informatization Development for my army opens a Science Explorations approach.

But, war is a complex gigantic system.The operational experiments of tradition deduction mode is difficult to meet the needs of experiment development. Along with information technology, mass computing machine technology and the fast development of emulation technology, in the way of analog simulation, realize operational experiments Becoming inexorable trend, the combination property of various countries' Combat Simulation System is the most constantly improving.After the Gulf War, the U.S. establishes The army evolutionary path of "-operational experiments-armed forces in real combat rehearsal-inspection under battle conditions of advancing a theory ".From U.S. army's air strike in 1989 Libyan " surgical strike ", to the Gulf War ground attack of 38 days and the Kosovo War big air strike of 78 days, From the air attack of Afghan War, shooting this Laden dead to marine corps, this " standard " tactics all originates from operational experiments. Other various countries also advanced most attention to operational experiments, operational experiments theory obtains great development.

For adapting to this inexorable trend of military science research and Practice Development, China studies operational experiments method the most energetically.Make War system is a kind of dynamic, nonlinear, has " emerging in large numbers " behavior and adaptivity, the complicated system of self-organization feature System.Based on this complex characteristics, the behavior of combat system to be carried out description the most true to nature it is necessary to accurately grasp and describe Relation between combat system moving law and internal all key elements thereof, uses advanced reasonably emulation technology, carries out operational experiments.

Yet with the complexity of war system, the utilization in operational experiments of the conventional emulation mode often also exists deficiency: People is in ring, part actual load in the emulation mode of ring, and the Realization of Simulation cost is high, difficulty is big, because of hardware facility limitation often only The Simulating Test Study of several aspect few in number can be carried out, it is difficult to expand the emulation experiment merit of complicated combat system further Energy；Emulation mode based on mathematical model, needs operation behavior is carried out mathematical abstractions, thus simplifies system whole The description of body behavior, have ignored the complexity hierarchy of combat system, it is difficult between true reflection various factors influence each other and with The effect of machine sexual factor；Method of Qualitative can not describe the dynamic process of operation, and lacks the self adaptation to Campaign Process Description with Self-organization；Fuzzy Simulation method processes observation data by fuzzy mathematics theory, but at Emulating in Combat System Simulation In, often due to the demonstration and verification of concept technology in advance of Information Battlefield, equipment architecture the side such as use and distribute rationally Face priori theoretical is insufficient, causes the observation data distortion obtained by priori theoretical, thus affects Fuzzy Simulation method Practical application effect；Though system dynamics processes some more complicated nonlinear problem with comparing visual pattern, but it is not Foot is a lack of comprehensive coordinate index system, and the process function of space factor, it is difficult to the space phase of each key element of describing system Interaction and feedback relationship.

Therefore, for solving above-mentioned technical problem, the object platform level Agent interactive simulation of a kind of innovation of necessary offer Unit of ground force operational experiments method, to overcome described defect of the prior art.

[summary of the invention]

For solving the problems referred to above, it is an object of the invention to provide the unit of ground force of a kind of object platform level Agent interactive simulation Operational experiments method, provides theoretical and method support for unit of high-resolution ground force operational experiments.

For achieving the above object, the technical scheme that the present invention takes is: the ground force of a kind of object platform level Agent interactive simulation Unit's operational experiments method, it is characterised in that: include unit of the ground force operational experiments of object platform level Agent interactive simulation Flow process, unit of the ground force operational experiments method for designing of object platform level Agent interactive simulation and mutual towards platform class Agent Unit of the ground force operational experiments development approach of emulation, wherein:

The flow process of unit of the ground force operational experiments of object platform level Agent interactive simulation: object platform level Agent is imitated alternately The operational experiments design of unit of genuine ground force is divided into three phases, i.e. the operational experiments experiment of object platform level Agent interactive simulation Design phase, operational experiments development phase and the object platform level Agent interactive simulation of object platform level Agent interactive simulation Operational experiments implement with the interpretation of result stage.

Unit of the ground force operational experiments method for designing of object platform level Agent interactive simulation: include the operation that task based access control decomposes The key element that experiment requirement acquisition method, the problem of operational experiments include with index Design method and operational experiments Military Scenario.

Unit of the ground force operational experiments development approach of object platform level Agent interactive simulation: include that object platform level Agent is handed over The operational experiments simulation scenario method for designing of emulation, platform class Agent modeling method, multi-platform level Agent interactive modeling mutually Method.

Compared with prior art, there is advantages that

The present invention is directed to the Complex Adaptive Systems characteristic of modern army operation, use based on platform class multi-Agent combat modeling with Emulation technology, is designed the basic procedure of unit of ground force operational experiments, main real to experimental design and experimental development etc. The implementation method testing procedure links is designed, and solves tradition operational experiments method and cannot meet complicated Emulating in Combat System Simulation The problem of experiment, provides theoretical and method support for unit of high-resolution ground force operational experiments.

[accompanying drawing explanation]

Fig. 1 is unit of the ground force operational experiments flow chart of object platform level Agent interactive simulation of the present invention.

Fig. 2 is the operational experiments requirement acquisition method schematic diagram that task based access control of the present invention decomposes.

Fig. 3 is the flow chart of Task-decomposing of the present invention.

Fig. 4 is the procedure chart of Task-decomposing of the present invention.

Fig. 5 is the present invention mapping process figure by the actual constituent element of combat system to Agent.

Fig. 6 is operational experiments problem framework figure of the present invention.

Fig. 7 is that the present invention fights index corresponding relation figure.

Fig. 8 is the operational experiments development process figure of object platform level Agent interactive simulation of the present invention.

Fig. 9 is that simulation scenario of the present invention forms structural framing figure.

Figure 10 is plate armour combined arms battalion command agent organization chart of the present invention.

Figure 11 is that Red Army of the present invention is to position defense blue force offensive action Agent interactive examples figure.

Figure 12 is the MAS communication blackboard model figure of Tank Formation of the present invention.

Figure 13 (a), 13 (b) is that the communication between Agent of the present invention affects comparison diagram to Agent sensing range.

Figure 14 (a), 14 (b) is that the communication between Agent of the present invention affects comparison diagram to Agent fighting range.

[detailed description of the invention]

With specific embodiment, the present invention is described in detail below in conjunction with the accompanying drawings.

A kind of unit of ground force operational experiments method of object platform level Agent interactive simulation, it is characterised in that: include towards flat The flow process of unit of the ground force operational experiments of platform level Agent interactive simulation, the unit of ground force of object platform level Agent interactive simulation Operational experiments method for designing and unit of the ground force operational experiments development approach towards platform class Agent interactive simulation.

1) flow process of unit of the ground force operational experiments of object platform level Agent interactive simulation

Operational experiments flow process is to describe operational experiments to carry out operational experiments research according to regular hour step or method step Process, divides operational experiments for stage.The unit of ground force of object platform level Agent interactive simulation is fought real by the present invention Test design and be divided into four-stage: experimental design, experimental development, experiment enforcement and interpretation of result, its flow process is as shown in Figure 1.

The experimental design stage mainly includes the content of four parts: emulation Requirement Acquisition, experiment problem design, experimental index set The design of meter, scenario, is substantially carried out the planning of experiment, specifies the purpose of operational experiments, determine experiment required solve problem, Basic assumption, index system, constraint and the strategy etc. taked.Experimental development is mainly built according to the condition determined Mould, realizes experimental development by the structure of platform class Agent physical model and interaction models, is divided into simulation scenario design thin Change, platform class Agent solid modelling and three parts of multi-platform level Agent interactive modeling.The principal set up implementation phase of experiment Condition carries out experiment and runs.The interpretation of result stage summarizes analysis according to experimental data.Being embodied as step is:

1. experimental design

Experimental design of the present invention mainly includes the content of four parts: emulation Requirement Acquisition, experiment problem design, experimental index Design, scenario design.

(1) the operational experiments Requirement Acquisition that task based access control decomposes.Operational experiments demand is divided into Definition of the existing problems demand, weighing apparatus Figureofmerit demand, scenario background demand and emulation demand.First carry out Task-decomposing and produce subtask, determine task institute The ability needed, proposes to solve the condition of task: entity and ability.By the Task-decomposing of based role, task institute will be completed The ability needed and Role Information are given to Agent, generate Agent, lay a good foundation for Agent modeling, obtain in this approach Experiment demand.

(2) carry out experiment problem design for Definition of the existing problems demand, in conjunction with armoured force of ground force be mainly used in Main way and The feature in flatter area, specifies operational experiments problem to be analyzed and related constraint, and proposing experiment needs the hypothesis of checking.

(3) design objective system.Design that propose according to problem it is assumed that design the index investigated required for solution problem.

(4) Combat scenario design.Operational experiments scenario is divided Military Scenario and simulation scenario.

2. operational experiments exploitation

Operational experiments development process of the present invention includes simulation scenario design refinement, platform class Agent solid modelling and multi-platform level Three steps of Agent interactive modeling.

(1) simulation scenario refinement is carried out.Formulating simulation scenario framework, design and simulation scenario is by operational organization relation, operation Entity and Campaign Process three part composition, describe emulation key element with this, lay the foundation for follow-up modeling work.

(2) platform class Agent solid modelling.Dependence and behavior two aspect are set out and are built Agent model.According to dividing before The subtask solved, has analyzed the fight capability of this required by task, sets up reconnaissance capability model, attacking ability model, motor-driven Capability model and communication capacity model.Operation is split as motor-driven, action, Action Selection rule, operation is total Become, motor-driven to mission area according to information, use Action Selection rule to perform corresponding behavior, complete combat duty.Set up The formal description model of Action Selection rule.

(3) multi-platform level Agent interactive simulation modeling.The Formal Representation cooperated by Agent and collaboration mode build many Platform class Agent coordination model, by confirming communication pattern, sets up information Perception model, completes to build traffic model.

2) unit of the ground force operational experiments method for designing of object platform level Agent interactive simulation

Unit of the ground force operational experiments design of object platform level Agent interactive simulation includes operational experiments Requirement Acquisition, operation The problem design of experiment, the index Design of operational experiments and Combat scenario 4 key steps of design.

1. operational experiments requirement acquisition method

The operational experiments requirement acquisition method that task based access control decomposes is as shown in Figure 2.Basic process is by studying operational experiments Combat duty in main body is decomposed, and has analyzed the operation needed for each subtask, therefrom finds, has determined Become the operation role of this task, with this role as prototype, generate Agent.

(1) unit's combat duty decomposition step

Unit's combat duty decomposition step is as shown in Figure 3.

The first step: overall tasks goal analysis.First analyze unit's combat duty to be studied, specify unit and complete fight The general requirement of task, weaves into and weaponry feature according to the structure of unit, has understood task work to be performed.

Second step: the structure for unit is weaved into and weaponry feature, and particularly it finally realizes target, has determined and has appointed Business and the related work carried out some basic principles to be adhered to.

3rd step: with target for traction, analyze and take rational angle to carry out Task-decomposing, be allowed to be more easy to reach target.

4th step: the flow process of unit's tactics method is decomposed.In actual operation, completing typically of overall combat duty Stage by stage, timesharing has saved.Unit is the most different in the action of task to be completed of different times and execution.Therefore to go deep into Refine the task in each time, be beneficial to the solution of task, be finally completed the Task-decomposing of unit's tactics method.Analyze son to appoint , in reality is fought, there is concurrency relation in time, ordering relation between each subtask, preferentially in the relation between business Precedence relationship in level, it is ensured that subtask has certain independence so that distribution task prevent task conflict.

5th step: analyze the enforceability of having been obtained of task by decomposition.Task has level, and different levels needs Different entities goes to solve, and the task of a certain level may not be solved by existing entity, is now accomplished by doing this task Further decompose.

6th step: according to Task-decomposing gained, sets up the overall task flow model that unit fights, total from unit's tactics method Body combat modeling benefit angle analysis, evaluates reasonability and the feasibility of this Task-decomposing, and optimized choice, and final structure is fitted The task structure hierarchy chart of cooperation war entity.

(2) the task distribution of based role

Total combat duty is decomposed into the achievable task of single optimal in structure or son that optimal in structure can cooperate is appointed After business, subtask is distributed to entity of fighting accordingly, the role served as in operation with this entity complete task ability and Operation characteristic is Agent model emulation demand, has i.e. carried out task ability and the distribution of entity role by task distribution, has entered And complete to obtain operational experiments emulation demand.In the present invention, the relation of task, role and Agent is as shown in Figure 4.

Combat duty is decomposed into optimal in structure and can independently or the subtask that cooperated it be appointed with completing this son by the present invention Operation role needed for business is mated, and the ability and self-role that complete this required by task are specifically fought energy by operation role Power gives Agent, makes Agent can perform action to complete the analog simulation of combat duty.The present invention quotes based on angle The concept of the Task-decomposing of color, by binding unit of corresponding ground force optimal in structure role, the mutual shape between role to Agent Become operational activity.Corresponding Agent is distributed to by operation entity to be served as afield the corresponding task of role with it, complete Become the task distribution of operational experiments.According to the hierarchical structure framework of object platform level interactive simulation Agent system, from the system that fights The process model that the actual role that unites maps to Agent, as shown in Figure 5.

2. operational experiments problem design

Complete operational experiments and first have to clear and definite operational experiments problem to be solved.The main task of experiment problem analysis is clear and definite Experiment target and problem is proposed, specify the border of the assumed condition of experiment problem, restrictive condition and problem, clearly test class Type and the basic skills intending employing.The framework of problem mainly sets up the structural description of the required operational experiments problem analyzed, Main description " what problem that operational experiments is to be solved is ".Designed by problem, first propose operational experiments problem, bright Field that really this problem may relate to, method, solving this problem can start with from which little problem.The work of unit's level War experiment, first has to the task mission that clear and definite unit is undertaken, feature of taking action, tactics main points etc.；Secondly, refer to according to operation The level waved, sets up the level target of problem analysis, and the Agent model of foundation can reflect that the operation of corresponding battlefield role is special Point, interactive simulation system can meet the needs of operational experiments；3rd, determine the empirical factor of problem, including controlled independent variable (i.e. empirical factor), uncontrollable independent variable and hypothesis and constraints etc., although unit fights, level is relatively low, but emulation Object is weapon platform, and the Indexes Comparison of the effects is complicated, and constraints is more, should rationally arrange experimental index；4th, Set up the relation between empirical factor and level target.Problem framework is as shown in Figure 6.

3. operational experiments index Design

Operation emulation experiment index is according to operational experiments demand, to testing the quantitative measurement that performance to be investigated is carried out.

(1) battle plan level index

Battle plan level index is the tolerance of the problem target to be reached that whole experiment to be checked or to be proved, and is that assessment is whole The basic index of individual experimental result.

Unit fights and is usually the task of completing in some time and area of space in higher level weaves into, and participates in the arm of the services less. But weighing the quality of battle plan, relation is intricate between each key element, it is difficult to quantitatively be given between each key element and combines usefulness pass System.We mainly index in terms of initial deployment and operation performance investigate battle plan: 1. operational time；2. oppose I fights and damages ratio；3. fight performance: triumph, failure；4. troops allocate: initial tank quantity, allowance of ammunition, attach troops to a unit Troops' weapons, fire support；5. consume: ammunition consumption, fuel consumption, armored clash are damaged (can repair and maybe can not repair), attached troops to a unit Troops consume.Quality from these index evaluation battle plans.

(2) operation level efficiency index

Combined operation action level efficiency index is used for weighing each operation of execution and completes the degree of task, is to weigh operation Index.Operation refers generally to motor-driven, scouting, information countermeasure, Strike, attack etc., or several action Comprehensively, the module of operation effect constitutes operation level effectiveness factors system, can investigate in terms of four: war Field perception, respond, attack and defense ability, sustainable fighting capacity.

(3) operation entity level capacity index

Operation entity level capacity index is the tolerance of technical performance of fighting operation entity in combat system.Operation entity includes making War tank, panzer, step battlebus, infantry, antitank firearm etc., several quality of these combat units and weaponry The module of war technical performance constitutes operation entity level index system.Behavioral competence representated by these indexs also direct body The operation behavioral competence of existing Agent, investigates these indexs equal to investigating the corresponding fight capability of Agent.

For single tank, its efficiency index directly affects the fighting efficiency of affiliated unit, and its fighting efficiency includes effectiveness Index and fight capability index, wherein fight capability index include firepower, motor-driven, protect and communicate.

(4) Agent individuality index

Due to the intelligent characteristic of Agent, the behavior of Agent is affected greatly by its individual character, even in object platform level Agent In the operational experiments of interactive simulation, it should Agent individuality index is classified as the experimental index of the analysis primarily looked at.As belligerent Property, look after friend side, near enemy, morale, individual character, quality etc., reality can be carried out by the individual setup measures of Agent Existing different feature individual for Agent, affects Agent and produces different behaviors.

Experimental index demand, and then design objective according to demand is obtained by Task-decomposing.On method axle, we are by appointing Business decomposition carry out index Design, embody task by senior complexity to rudimentary simply, experimental index is by extensive thin process.? On working shaft, then it it is the process generating Agent.Corresponding relation between them is as shown in Figure 7.

4. Combat scenario design

Combat scenario key element includes:

(1) essential of battlefield environment

Battlefield surroundings is emulation environmental key-element residing for operation both sides, has both included that natural environment also included social environment, electromagnetism ring Border etc..

Natural environmental elements is the key elements such as the landform residing for battlefield, weather, including 1. landform: landform height fluctuating, water system, The atural objects such as road, vegetation, residential block；2. weather: temperature, humidity, weather conditions, wind speed, visibility etc.；3. fight Scope: central point, scope etc..Natural environment is the basic environment residing for Combat counterwork both sides, and the operation to combat unit is imitated Can have a significant impact.

Social environment is the social circumstance of their location, battlefield, specifically includes that combat area economy, common people's religions belief, political affairs Control tendency, attitude etc. to operation both sides.

Electromagnetic environment refers mainly to the electromagnetic environment that the use of civilian installation and military applications is caused.

(2) operation key element

1. the posture of operation

The posture of operation is to reflect current battlefield enemy's situation, understands the approach of the situation that operational front faces.

Operational strength: operation both sides troops quantity.

Tactical disposition: both sides' deployment of forces region and type.

The purpose of operation: both sides fight purpose.

2. combat duty

Combat duty is the main body of Military Scenario, and Military Scenario launches around combat duty, provides the story of a play or opera for emulation antagonism, It it is the main source of emulation data.

The type of combat duty: assault the main target, assist, depth is attacked, it is roundabout to intert, defend, scout, attack etc..

Complete the time limit: complete the time limit of task, the place captured at the appointed time or the anti-place observed or late Stagnant enemy etc., according to being described in Military Scenario.

The troops of participation task: both sides troops red, blue, weapons.

Mission area: mission area scope.

3. optimal in structure

Optimal in structure is the description to combat unit, is by primary entity and the carrier of weapon of emulation antagonism.

The type of platform: tank, panzer, infantry, rocket launcher etc..

The mark of platform: have multiple in operation with type of platform, therefore sets each optimal in structure in scenario describes Fixed unique mark, it is simple to identify and in Campaign Process, it carried out manual intervention.

Positional information: the coordinate of platform, translational speed, direction and route etc..

Belonging to side's mark: red or blue party or lead tune.

Weapon performance: range, firing rate, hazard boundary, controllable velocity, protective capacities etc..

Communication capacity: communication distance, communication mode, capacity of resisting disturbance etc..

3) unit of the ground force operational experiments development approach of object platform level Agent interactive simulation

Unit of ground force operational experiments development process such as Fig. 8 of object platform level Agent interactive simulation.With Military Scenario as background, According to experiment problem, index of correlation, refine simulation scenario, with simulation scenario as foundation, construction platform level Agent model and Multi-platform level Agent interaction models.

1. the operational experiments simulation scenario design of object platform level Agent interactive simulation

(1) operational experiments simulation scenario composition

Simulation scenario, is the demand according to Combat Simulation System, according to operation contrived experiment system, to the attempt of operation both sides, Campaign Process, fight in the imagination made of situation about being likely to occur and operation entity main activity in Campaign Process and vacation Fixed.

Simulation scenario is with Military Scenario as foundation, and Simulation-Oriented system developer, according to emulation needs of fighting, design is fought Experiment simulation object and the story of a play or opera, the basic foundation of exploitation operational experiments analogue system.The design of simulation scenario is mainly from following three Individual key element is started with: operational organization relation, operation entity, Campaign Process.Operational organization relation is each belligerent under Military Scenario The mutual relation of entity, the member in relation is the main carriers of Campaign Process control command stream.Operation entity is to play the part of in operation The reality drilling certain role is abstract, is the basis of model construction.Campaign Process is the core of master-plan, is to build to emulate The basic framework of journey.But these three key element cannot be directly used to simulation scenario, simulation modeling should be converted into and programming personnel is permissible The form understood.These three key element is converted into corresponding three parts by the present invention: multi-Agent membership credentials, platform class are made War entity agent, multi-agent computing system, form simulation scenario.Simulation scenario composition structure is as shown in Figure 9.

(2) core content of operational experiments simulation scenario design

1. membership credentials structure describes

In unit of ground force, the relation between usual combat unit includes: accuse relation and cooperation relation.

Command system and unit according to conventional unit weave into situation, it is considered to the general cooperative operations of conventional unit, its entity The organizational structure of Agent battle model system should at least be sought, connects, arranged, and the multilamellar even needing the class of more subordinate to work out is mixed Box-like fabric architectures.As a example by the armoring combined arms battalion that army of various countries generally works out, list main battle weaponry is considered as basic granularity Unit, seeks as the highest commander's unit, even, row be temporary location, they are behavior entity agents relative to higher level, now Its all subordinates all can be regarded as being aggregated under general frame, is again commander's entity agent relative to subordinate.

In Campaign Process, command entity Agent is the decision-making fought and commander's unit, by battle plan to next stage operation Command entity Agent assigns, and meanwhile, next stage operational commanding entity agent performs as upper level operation behavior entity again Corresponding combat duty, and operation situation is reported to upper level command entity Agent, for upper level command entity Agent Decision-making foundation is provided.Its organizational structure is as shown in Figure 10: same weave into interior higher level's command entity and there is subordinate's operation entity Commander's control planning, if combined arms battalion command agent is to Reconnaissance Company command agent, now single the most upper and lower Level belongs to the category of centralized organizational structure.Interior lower floor's operation entity is weaved into, under Reconnaissance Company command agent same Combat Reconnaissance Platoon command agent and special reconnaissance row's command agent, belong to distributed organization structure from the perspective of peer Category.So, the overall Agent operation interbehavior organizational structure of this plate armour combined arms battalion is a typical hybridized group Knit structure.

2. the process prescription of multi-agent computing system

Campaign Process in the operational experiments system of object platform level Agent interactive simulation is exactly mutual between platform class Agent Process.The most intricate owing to fighting, in operational experiments, multi-agent computing system presents more complicated relation, in order to It is easy to distinguish, as a example by armored motor unit fights, can be combat unit's inside interacting activity in combat system, such as information The abstract interacting activity carried out for order of interacting activity between perception Agent, command tank Agent, battle tank Agent； Can be combat unit and outside interacting activity, such as information Perception Agent, commander control agents, Strike Agent On interacting activity abstract be outside distribution interacting activity.In order to the process prescription method of multi-agent computing system is described, with red As a example by side is to position defense blue party offensive action.

Figure 11 gives the overall interaction models that the blue party unit of position defense implements offensive combat operation with red unit.For letter Change problem, blue party unit only represents with blue party defence Agent here, red unit with have employed three roles, Information Perception Agent, command tank Agent, battle tank Agent represent.Around the antagonism of attack Yu defence, both sides It is mutual that unit will carry out a series of antagonism, only describe a kind in the drawings, this alternately: red blue both sides resist alternately, It is embodied in both sides' Strike and associated activity.

Just mutual owing to there occurs between red blue antagonism both sides' system, correspondingly, red blue both sides are in order to adapt to this mutual sending out Raw, also can carry out inside respective system a series of alternately.Such as, defensive disposition and the firepower of blue party defence Agent is strikeed back Deng behavior cause mutual, red combat system-of-systems is in order to adapt to the impact caused of these interbehaviors, in red combat system-of-systems Portion carried out following 3 kinds mutual: the information that information Perception Agent and command tank Agent, battle tank Agent are carried out Exchange；The scouting situation that battle tank Agent administrative with it for command tank Agent is carried out reports, strike task is assigned； The strike effect feedback that battle tank Agent and commander's control agents are carried out.

2. platform class Agent modeling

(1) attack model

The tank of armored motor unit's operation, rifle, rocket launcher etc. are all directly to take aim at weapon, and therefore we only study and directly take aim at attacking of weapon Hit ability behavior.Here, it is contemplated that aggressive behavior is that i.e. aggressive behavior is by two parts to the other side's emission bullet or shell Composition: hit and injure target.

The kinetic energy directly taking aim at weapon Main Basis bullet acts on target, if the hit probability of main body weapon is P_H, injuring probability is P_K, injuring probability is a function about shooting distance

$P_K=\underset{0}{\overset{2\mathrm{\π}}{\∫}}\underset{0}{\overset{R}{\∫}}\frac{1}{2{\mathrm{\π\σ}}^2}\exp (-\frac{r^2}{2{\mathrm{\σ}}^2})rdrd\mathrm{\θ}=1-\exp (-\frac{R^2}{2{\mathrm{\σ}}^2})$

R is the radius of damage, and σ is standard error.

(2) Detection model

Scout the optics being primarily referred to as utilizing optical reconnaissance equipment or radar-reconnaissance equipment to carry out or radio intelligence etc., scout energy Force modeling includes findings that can force modeling and resolution capability modeling.

1. ability of discovery modeling

In reality is fought, scouter and spot are generally all in kinestate, and the method building ability of discovery model is detectd The person of examining is initial point, as object of reference, observes the moving line Z relative to scouter of spot, if the seat of point on Z It is designated as (α (t), β (t)):

Scouter with the distance of spot is

$R\left(t\right)=\sqrt{\left({\mathrm{\α}}^2\right(t),{\mathrm{\β}}^2(t\left)\right)}$

As t=0, spot is at position A₀(α₀, β₀), and along Z curve setting in motion, sent out in t spot Existing probability is

$P\left(t\right)=1-\exp (-{\∫}_0^t\mathrm{\γ}(t\left)dt\right)$

In formula: condition probability of detection γ (t) is the function of spot move distance.Order

$G\left(t\right)={\∫}_0^t\mathrm{\γ}\left(t\right)dt$

Then G (t) is referred to as the discovery gesture of target.Then

P (t)=1-exp (-G (t))

If being scouted the relative motion curve Z of object by Z₁(A₀A₁) and Z₂(A₁A₂) composition, to Z₁For, the discovery of target Gesture is

$G_1\left(t\right)={\∫}_0^{t_1}\mathrm{\γ}\left(t\right)dt$

To Z₂, the discovery gesture of target is

$G_2\left(t\right)={\∫}_{t_1}^{t_2}\mathrm{\γ}\left(t\right)dt$

Then to Z=Z₁+Z₂, find that gesture is

$G={\∫}_0^{t_2}\mathrm{\γ}\left(t\right)dt={\∫}_0^{t_1}\mathrm{\γ}\left(t\right)dt+{\∫}_{t_1}^{t_2}\mathrm{\γ}\left(t\right)dt=G_1\left(t\right)+G_2\left(t\right)$

2. resolution capability modeling

It is known that when target arrives certain value with our distance, and we could carry out identification to target, obtain target Information.In reconnaissance operations, this distance value is exactly to scout the distance between Agent and spot, and this is a constant, It is relevant with the technical performance of Reconnaissance Equipment, in this distance range, scouts Agent and with identification spot, and can obtain Taking relevant information, it is set as scouting resolution threshold θ by we.If the maximum reconnaissance range of platform class Agent is S_max, Scout Agent and by scout object distance be D, then resolution capability model can be expressed as:

If D≤0

Scout Agent and can distinguish the kind of spot and technical performance of typically fighting；

Else if θ ＜ D≤S_max,

Scout Agent and can distinguish that the enemy and we of spot belong to situation；

Else if D ＞ S_max,

Scouting Agent can not identification or observe spot.

(3) maneuver modeling

1. follow the trail of

Assume to follow the trail of n target Agent, wherein, locus coordinate, speed and the acceleration of target Agenti in t Degree is respectivelyWithTracking Agent is w to the urgent weight of tracking of Agenti_i, w_iReflect and follow the trail of the Agent tracking pressing degree to target Agenti, therefore 0≤w_i≤ 1, w_i∈ R, 1≤i≤n, i ∈ N.Now, the determination process of maneuvering target point is as described below.

Follow the trail of the Agent motor-driven stroke of maximum possible within the Δ t timeOrder R_cs=min (R_m, R_s)。

Order

$ty=\underset{i=1}{\overset{n}{\Σ}}{w}_i\·(y_t^i+v_y^i(t)\·\mathrm{\Δ}t+{\∫}^{i+\mathrm{\Δ}t}{\∫}^{i+\mathrm{\Δ}t}{a}_y^i(t)\·{\mathrm{dt}}^2)$

IfThen solve following with x_d、y_dEquation group for unknown number

$\left\{\begin{array}{c}\frac{y_d-ty}{x_d-tx}=\frac{y_t-ty}{x_t-tx}\\ \sqrt{{(x_d-x_t)}^2+{(y_d-y_t)}^2}=R_{cs}\end{array}\right.$

Otherwise make x_d=tx, y_d=ty

2. dodge

Assume total n target Agent in the target group that t is hidden, wherein, the space bit of target Agenti Put coordinate, speed and acceleration to be respectivelyWith, dodge Agent and it dodged Urgent weight is w_i, now, the calculating process dodging the motor-driven direction of Agent is as follows.

When meeting veil, and target is when opposite side is close to veil, dodges Agent and may select fast approaching veil, Now dodge Agent to move in the same direction with target Agenti, when there is no veil, dodge Agent and answer wide, now Dodge Agent to move dorsad with target Agenti.Therefore

$d_x=-sig(\underset{i=1}{\overset{n}{\Σ}}{w}_i\·x_t^i-x_t)\·\underset{i=1}{\overset{n}{\Σ}}{w}_i\·\left(v_x^i\right(t)+a_x^i(t\left)\right)$

$d_y=-sig(\underset{i=1}{\overset{n}{\Σ}}{w}_i\·y_t^i-y_t)\·\underset{i=1}{\overset{n}{\Σ}}{w}_i\·\left(v_y^i\right(t)+a_y^i(t\left)\right)$

$\left\{\begin{array}{cc}\mathrm{\&theta;}=ar\cos \left(\frac{d_x}{\sqrt{d_x^2+d_y^2}}\right)& d_y\&GreaterEqual;0\\ \mathrm{\&theta;}=-ar\cos \left(\frac{d_x}{\sqrt{d_x^2+d_y^2}}\right)& d_y<0\end{array}\right.$

θ is the x-axis positive direction angle to the motor-driven direction of operation Agent of battle space coordinate.

(4) traffic model

Communication, is the activity carrying out communication for information between Agent and other Agent.Agent uses messaging information. Different types of message, the information content of transmission is different, and during belligerent, message commonly used for Agent has:

Command messages: task identification, the participation weaponry of task, attack pattern, target location etc..

Scout message: scout gained information, such as enemy's deployment, weaponry situation, troops' size etc..

Motor-driven message: maneuvring route, target location coordinate etc..

Attack message: object of attack position coordinates, quantity, weaponry etc..

Feedback message: the feedback after execution action, as eliminated enemy's quantity, our Casualty Vulnerability Number etc. in attack action.

The most multi-platform grade of Agent interactive modeling

(1) multi-Agent cooperation model

The coordination model formalization of multi-platform level Agent is expressed as follows:

M=<Ag, G, P, T, S>

Wherein: Ag represents platform class Agent.Being divided into two kinds, one is that cooperation participates in Agent, and one is to send cooperation to advocate The cooperation of view sends Agent.Cooperation sends Agent and proposes cooperation proposal, and the son to be done according to realizing cooperation target Task is allocated planning；Then screen, according to the ability with the candidate Agent participating in cooperation intention, the participation that suitably cooperates Agent。

G represents cooperation target, cooperation send Agent and propose according to the demand completing task.

P represents Collaborative planning, it is important to according to the subtask structure of completing needed for realization cooperation target of task, and determined Ability needed for becoming each subtask, possess the platform class Agent of this ability, complete the priority level of subtask, and respectively The mutual relation of platform class Agent.

T represents the set of the Agent participating in cooperation, Ag ∈ T.

S represents cooperation scheme, is the task division of labor between cooperation participation Agent and coordinated scheme, S ∈ P.

(2) multi-platform level Agent Communication Pattern Model

Use during communication between the private mortgage loan in object platform level Agent interactive simulation system and point-to-point tie mutually with blackboard model The communication connection means closed, when top layer combat duty order is assigned, operational environment is issued and is used blackboard model, group member While self combat duty clear and definite, additionally it is possible to understand in time friendly neighbour and fight the theater of war environment of Agent, be beneficial to overall Completing of combat duty；Bottom operation Agent uses point-to-point messaging method in collaborative processes, is beneficial to fight and appoints The disguise of business.As shown in figure 12.

(3) multi-Agent information Perception model

Agent interacts, and the information to external world that first has to carries out perception.Each except in self perception environment of each Agent Item information, also receives the information data of other Agent transmission or asks for for information about to other Agent, strengthening self information Perception, increases obtained information quantity, also can expand fighting range simultaneously.Information Perception model is that current Agent is to other The attention degree of the information data that Agent gathers, it can be shared information and be converted into individual cognition by Agent, is applied to mobile During the penalty of position calculates, i.e. turning to the degree of decision superiority, its penalty is:

$Z_{G_A(x,y)}=Z_{A_0(x,y)}+{\mathrm{\&omega;}}_{comm}{Z}_{comm}(x,y)$

WhereinFor current Agent according to self perception information calculate (x, penalty numerical value y), i.e. according to from The decision behavior that body perception is done.Z_comm(x, y) according to share the penalty numerical value that information calculates, i.e. share information certainly Plan behavior, weighted value ω_commFor the current Agent attention degree to shared information, can between 0-1 value.ω_comm=0 table Show all of shared information of ignorance, do not affect decision-making.ω_comm=1 represents the most cognitive shares information, as the reference of decision-making.

As shown in Figure 13 (a), when working as two Agent of A, B without communication linkage, the sensing range S of A_G(shade Part) it is limited only to himself sensing range, i.e. S_A

S_G=S_A

As shown in Figure 13 (b), work as after two Agent of A, B have communication linkage, the overall sensing range S of A_G(shade Part) it is two Agent sensing range (S_A, S_B) sum, i.e.

S_G=S_A∪S_B

As shown in Figure 14 (a), when working as two Agent of A, B without communication, if R_s、R_fBe respectively A sensing range and Firepower scope, the fighting range R of A_eFor

R_e(A)=R_s(A)∩R_f(A)

As shown in Figure 14 (b), working as A, after B establishes a communications link, the fighting range of A also will be enlarged by R_eFor:

R_e(A)=(R_s(A)∪R_s(B))∩R_f(A)

Above detailed description of the invention is only the preferred embodiment of this creation, not in order to limit this creation, all in this creation Spirit and principle within any modification, equivalent substitution and improvement etc. done, should be included in this creation protection domain it In.

Claims (1)

1. unit of the ground force operational experiments method of an object platform level Agent interactive simulation, it is characterised in that: include face To the flow process of unit of the ground force operational experiments of platform class Agent interactive simulation, the land of object platform level Agent interactive simulation Unit of army operational experiments method for designing and unit of the ground force operational experiments development approach towards platform class Agent interactive simulation, Wherein:

The flow process of unit of the ground force operational experiments of object platform level Agent interactive simulation includes: by object platform level Agent Unit of the ground force operational experiments design of interactive simulation is divided into three phases, i.e. the operation of object platform level Agent interactive simulation Experiments experiment design phase, operational experiments development phase and object platform level Agent of object platform level Agent interactive simulation The operational experiments of interactive simulation is implemented and the interpretation of result stage；

Unit of the ground force operational experiments method for designing of object platform level Agent interactive simulation includes: the work that task based access control decomposes The key element that war experiment requirement acquisition method, the problem of operational experiments include with index Design method and operational experiments Military Scenario；

Unit of ground force of unit of the ground force operational experiments development approach of object platform level Agent interactive simulation includes: object platform Level the operational experiments simulation scenario method for designing of Agent interactive simulation, platform class Agent modeling method, multi-platform level Agent Interactive modeling method.