Scalable Combat Mission Planning Simulation Method, System, Device and Medium

Abstract

The present invention provides an extensible combat mission planning simulation method, system, device and medium, which relates to the technical field of computer combat simulation. The method includes: defining a rule template in a combat mission planning system, configuring rule parameters in the rule template, and generating a specific first rule instance according to the configured parameter values; decomposing the first rule instance into multiple element components according to specific functions, and combining the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; adopting a behavior modeling method of a behavior tree to perform logical configuration on the constructed second rule instance adapted to a specific combat scenario to obtain a combat rule adapted to a specific combat scenario. The present invention provides a convenient rule editing and extension method to achieve the editability and extensibility of rules, improve the adaptability of the system to diverse combat scenarios, and provide more powerful support for combat command decision-making.

Description

Technical Field

[0001] The present invention relates to the technical field of computer combat simulation, and particularly relates to an extensible combat mission planning simulation method, system, device and medium. Background Art

[0002] In the combat mission planning at the system level, battlefield elements are extremely complex. From the perspective of the geographical environment, it covers different terrain features such as mountains, plains, waters, etc. Each terrain has different impacts on combat operations. For example, mountains affect the maneuver speed of troops and the transmission quality of communication signals, while waters limit the action range of land equipment. In terms of military forces, it involves multi-domain combat forces in land, sea, air, space, and cyber, and the coordination relationships among these forces are complex. At the same time, the battlefield space changes complexly. During the combat process, the combat area may rapidly expand or shrink, and the combat focus will also quickly shift.

[0003] There are many problems in the model construction of existing combat mission planning systems. On the one hand, due to the complex changes in the battlefield space to be processed, it is extremely difficult to judge various situations and design corresponding disposal rules in experiments. For example, when facing a sudden electronic interference launched by the enemy, the system needs to quickly judge the type, intensity, range, etc. of the interference, and make disposal decisions such as switching communication frequencies and enabling backup communication links according to the corresponding rules. This process involves a large amount of complex judgment logic and disposal rule design. On the other hand, related software designs and data are often customized for specific applications. If the system design does not fully consider the user's ability to customize and expand, subsequent applications and expansions will be severely restricted. For example, when the combat scenario changes and new weapons and equipment or combat concepts appear, the system cannot easily adjust rules and expand functions, and it is difficult to adapt to diverse combat requirements.

[0004] Tactical rules and command and control rules, as the basis for the system model to execute combat operations and command decisions, are one of the decisive influencing factors for the combat mission planning system to obtain simulation conclusions. However, most current systems lack editable and extensible support for these rules during the system operation stage, resulting in insufficient flexibility and adaptability of the system. Summary of the Invention

[0005] In view of this, the embodiments of the present application provide an extensible combat mission planning simulation system, which realizes the editability and extensibility of rules by providing a convenient way for rule editing and extension, improves the adaptability of the system to diverse combat scenarios, and provides more powerful support for combat command decisions.

[0006] The embodiments of the present application provide the following technical solutions: An extensible combat mission planning simulation method, including:

[0007] Define a rule template in the combat mission planning system, configure rule parameters in the rule template, and generate specific first rule instances according to the configured parameter values; wherein, the rule template includes a rule name, a rule description, a rule parameter list, and a logical relationship, and the rule parameters include battlefield environment condition parameters, combat unit status parameters, and tactical response parameters;

[0008] Decompose the first rule instance into multiple element components according to specific functions, and combine the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein, the element components include condition element components, status element components, and response element components;

[0009] Adopt the behavior modeling method of a behavior tree to perform logical configuration on the constructed second rule instance adapted to a specific combat scenario to obtain a combat rule adapted to a specific combat scenario.

[0010] According to an embodiment of the present application, after constructing a second rule instance adapted to a specific combat scenario, it further includes:

[0011] Detect conflicts in the condition part and the response part of multiple rule instances. If there are rule conflicts, calculate the priorities of the conflicting rules respectively, and determine the execution order of the conflicting rule instances according to the priorities; wherein, the detection of the condition part includes numerical range conflict detection and logical relationship conflict detection, and the detection of the response part includes resource competition conflict detection and action sequence conflict detection.

[0012] According to an embodiment of the present application, the priority calculation formula of the rule is as follows:

[0013]

[0014] In the formula, P is the priority score of the rule, W i is the weight of the i-th parameter in the rule, indicating the degree of influence of the parameter on the rule priority, S i is the status value of the i-th parameter, indicating the specific value or score of the parameter in the current battlefield environment, n is the total number of parameters in the rule, T is the time decay factor, indicating the time sensitivity of the rule, M is the task target matching degree, indicating the degree of fit between the rule and the current combat mission target, and α, β, and γ are the weight coefficients of each dimension, satisfying α + β + γ = 1.

[0015] According to an embodiment of the present application, the process of the resource competition conflict detection includes:

[0016] Establish a resource allocation table, and record the status information of each resource in the resource allocation table. The status information includes the current usage status of each resource, the corresponding allocation rule, and the allocation quantity information;

[0017] Construct a conflict matrix with different rules as rows and columns respectively, traverse the conflict matrix, make a judgment according to the resource allocation table to determine whether there is a conflict in the use of the same resource by two rules. If there is a conflict, mark it at the corresponding position in the matrix;

[0018] Traverse the conflict matrix regularly or when the rules are updated, and detect the conflict marks in the conflict matrix.

[0019] According to an embodiment of the present application, the process of detecting the conflict of action sequence includes:

[0020] Number each combat action in the same combat scenario and define the dependency relationship between each combat action;

[0021] Construct an action sequence for the combat actions involved in each rule according to the mutual dependency relationship and the corresponding number sequence;

[0022] Detect the action sequences of different rules to judge whether the action sequences of different rules are consistent with the predefined action dependency graph. If they are not consistent, it is determined that there is a conflict in the action sequence.

[0023] According to an embodiment of the present application, adopt the behavior modeling method of the behavior tree to perform logical configuration on the constructed second rule instance adapted to a specific combat scenario, including:

[0024] Define the structure of the behavior tree, configure the control nodes, condition nodes, action nodes and connection nodes of the rules in the structure of the behavior tree, and configure the logic between each node to obtain the combat rules adapted to a specific combat scenario.

[0025] According to an embodiment of the present application, the method further includes:

[0026] Generate a rule version for the reconfigured combat rules adapted to a specific combat scenario to record the change information of the rules, where the change information includes the change time, the person who made the change, and the change content.

[0027] The present application also provides an extensible combat mission planning simulation system, including:

[0028] A rule parameter configuration module for defining a rule template in the combat mission planning system, configuring rule parameters in the rule template, and generating a specific first rule instance according to the configured parameter values; wherein, the rule template includes a rule name, a rule description, a rule parameter list and a logical relationship, and the rule parameters include battlefield environment condition parameters, combat unit status parameters and tactical response parameters;

[0029] A rule decomposition and construction module, which is used to decompose the first rule instance into multiple element components according to specific functions, and combine the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein, the element components include a condition element component, a status element component, and a response element component;

[0030] A rule logic configuration module, which is used to perform logic configuration on the constructed second rule instance adapted to a specific combat scenario by using the behavior modeling method of a behavior tree to obtain a combat rule adapted to a specific combat scenario.

[0031] This application also provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the scalable combat mission planning simulation method described above is implemented.

[0032] This application also provides a computer-readable storage medium, which stores a computer program for executing the scalable combat mission planning simulation method described above.

[0033] Compared with the prior art, the beneficial effects that can be achieved by at least one of the above technical solutions adopted in the embodiments of this specification at least include: Through rule parametric modeling in the embodiments of the present invention, users can quickly adjust rule parameters according to real-time battlefield intelligence, enabling the system to adapt to different combat scenarios and providing timely and effective decision-making support for combat command. By combining component-based modeling and behavior tree behavior modeling, it is convenient for users to add, delete, or modify rule components, realizing the dynamic expansion of rules, enabling the system to more accurately simulate complex battlefield environments and combat behaviors, and improving the accuracy and reliability of simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of this application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0035] Figure 1 It is a schematic flowchart of the scalable combat mission planning simulation method according to the embodiments of the present invention;

[0036] Figure 2 It is a schematic structural diagram of the scalable combat mission planning simulation system according to the first embodiment of the present invention;

[0037] Figure 3 It is a schematic structural diagram of the scalable combat mission planning simulation system according to the second embodiment of the present invention;

[0038] Figure 4 It is a schematic structural diagram of the computer device of the present invention. Specific embodiments

[0039] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0040] The following uses specific specific examples to illustrate the implementation manners of the present application. Those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without making creative efforts belong to the scope of protection of the present application.

[0041] As Figure 1 shown, the embodiments of the present invention provide an extensible combat mission planning simulation method, including:

[0042] S101. Define a rule template in the combat mission planning system, configure rule parameters in the rule template, and generate a specific first rule instance according to the configured parameter values; wherein, the rule template includes a rule name, a rule description, a rule parameter list, and a logical relationship, and the rule parameters include battlefield environment condition parameters, combat unit status parameters, and tactical response parameters;

[0043] S102. Decompose the first rule instance into multiple element components according to specific functions, and combine the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein, the element components include condition element components, status element components, and response element components;

[0044] S103. Adopt the behavior modeling method of a behavior tree to perform logical configuration on the constructed second rule instance adapted to a specific combat scenario to obtain a combat rule adapted to a specific combat scenario.

[0045] In the embodiments of the present invention, by introducing parametric modeling, component-based technology, and behavior tree modeling methods, the editability and extensibility of the rules of the combat simulation system are realized. The rule parameters can be flexibly configured according to specific requirements to adapt to different simulation scenarios; through parametric modeling, the system can easily expand new rule templates and parameters. Through component-based modeling technology, rule components can be conveniently added, deleted, or modified to achieve the dynamic expansion of rules. Through parametric modeling and component-based technology, the system can more accurately simulate complex battlefield environments and combat behaviors, improving the reliability of simulation results.

[0046] In specific implementation, in S101, using the parametric modeling technology of the rule model, first define a rule template in the system. The rule template includes rule name, rule description, parameter list, logical relationship, etc. Extract the key factors in the rule as parameters for configuration to generate a specific rule instance. For example, in the rule for judging the threat level of enemy air raids, key factors such as the number of enemy fighter jets, flight speed, and weapon mounting types are set as parameters. In the system operation stage, according to the actual combat scenario, the rule can be instantiated and customized by configuring these rule parameters. For example, in different combat areas, the deployment of enemy air power is different. According to intelligence information, parameters such as the number of enemy fighter jets can be adjusted to make the rule more suitable for the current combat situation, so as to accurately judge the threat level of air raids.

[0047] In specific implementation, in S102, through component-based modeling technology, the rule is split into finer-grained elements such as conditions, states, responses, etc. By means of dragging, combining, etc., different rule components are combined into a complete rule; each component is responsible for a specific function, and components can be added, deleted, or modified according to needs. Specifically, taking the rule for dealing with the attack of enemy ground forces as an example, the condition elements may include the attack direction, troop strength scale, equipment type, etc. of the enemy forces; the state elements may involve the strength of our defense position, the state of defensive troops, etc.; the response elements include the counterattack strategies and troop deployment plans taken by us. By combining these different elements, a rule suitable for a specific combat scenario can be constructed. When the combat scenario changes, the combination of each element can be flexibly adjusted to quickly generate a new rule. For example, if the enemy changes the attack direction, the attack direction parameter in the condition element can be adjusted, and the troop deployment strategy in the response element can be adjusted accordingly to construct a new response rule.

[0048] In some embodiments of the present invention, after constructing the second rule instance adapted to a specific combat scenario, it further includes:

[0049] Conflict detection is performed on the condition parts and response parts in multiple rule instances. If there are rule conflicts, the priorities of the conflicting rules are calculated respectively, and the execution order of the conflicting rule instances is determined according to the priorities. Among them, the detection of the condition part includes numerical range conflict detection and logical relationship conflict detection, and the detection of the response part includes resource competition conflict detection and action sequence conflict detection.

[0050] When multiple rules are generated and when multiple rules simultaneously meet the trigger conditions, conflicts may occur, resulting in the system being unable to determine which rule to execute. To solve this problem, the embodiments of the present invention propose a rule conflict detection and solution method, which ensures that the system can efficiently and reasonably handle rule conflicts through a conflict detection algorithm and priority calculation. Specifically, rule conflicts are mainly divided into the following two categories: 1. Condition conflict: The condition parts of multiple rules overlap or are exactly the same, resulting in simultaneously meeting the trigger conditions. 2. Response conflict: There are contradictions in the response parts of multiple rules.

[0051] The condition conflict includes numerical range conflict detection and logical relationship conflict detection. (1) Numerical range conflict detection: In the rules of the combat mission planning system, many conditions are defined by numerical ranges, such as target distance, number of troops, etc. The system uses an interval comparison algorithm for detection. Specifically, when implementing, traverse all the rules involving numerical range conditions. For each numerical range condition in a rule, such as (a1, b1), compare it with the same type of numerical range condition (a2, b2) in other rules. If the numerical ranges overlap, it is considered that there is a numerical range conflict. (2) Logical relationship conflict detection: There may also be logical conflicts in the conditions in the rules, which can be specifically detected by using Boolean logic reasoning; for example, parse the conditions in the rules into logical expressions, convert the conditions described in natural language into Boolean logical expressions, and use logical reasoning rules to check whether there are contradictory cases in the logical expressions.

[0052] The response conflicts include resource competition conflict detection and action sequence conflict detection. (1) Resource competition conflict detection: During the execution of combat missions, different rules may put forward conflicting usage requirements for the same resource. For example, multiple rules may simultaneously compete for limited ammunition resources or communication channel resources. Specifically in implementation, the system can detect through a resource allocation table and a conflict matrix. Specifically, it includes: establishing a resource allocation table, recording the status information of each resource in the resource allocation table, where the status information includes the current usage status of each resource, the corresponding allocation rules, and the allocation quantity information; constructing a conflict matrix with different rules as rows and columns respectively, traversing the conflict matrix, and making a judgment according to the resource allocation table to determine whether there is a conflict in the usage of the same resource by two rules. If there is a conflict, mark it at the corresponding position in the matrix; regularly or when the rules are updated, traverse the conflict matrix and detect the conflict marks in the conflict matrix. (2) Action sequence conflict detection: Combat actions have certain requirements for the sequence. Multiple rules may conflict in the combat action sequence. Specifically in implementation, the system detects by establishing an action dependency graph. Specifically, it includes: numbering each combat action in the same combat scenario, such as numbering A1, A2, and defining the dependency relationship between each combat action, such as A2 depends on A1, that is, A1→A2; constructing an action sequence for the combat actions involved in each rule according to the mutual dependency relationship and the corresponding numbering order; detecting the action sequences of different rules to determine whether the action sequences of different rules are consistent with the predefined action dependency graph. If they are not consistent, it is determined that there is an action sequence conflict.

[0053] The embodiment of the present invention solves the rule conflict problem based on priorities. The priority calculation formula of the rules is as follows:

[0054]

[0055] In the formula, P is the priority score of the rule, W i is the weight of the i-th parameter in the rule, indicating the influence degree of this parameter on the rule priority. This parameter can be set according to experience or learned from historical data through a machine learning algorithm; S i is the status value of the i-th parameter, indicating the specific value or score of this parameter in the current battlefield environment. n is the total number of parameters in the rule, and T is the time decay factor, indicating the time sensitivity of the rule, and the priority gradually decreases over time; the time decay factor T can be calculated through this formula, , where λ is the attenuation coefficient, which is used to control the rate at which the priority decays over time, and t is the time interval from when the rule was created to the current moment. M is the task objective matching degree, which represents the degree of fit between the rule and the current combat task objective. The higher the matching degree, the higher the priority, and it can be obtained by the ratio of the number of matching parameters between the rule and the task objective to the total number of parameters of the task objective; α, β, and γ are the weight coefficients of each dimension, satisfying α + β + γ = 1.

[0056] The embodiments of the present invention can reduce the computational complexity while ensuring the accuracy of priority calculation, and improve the practicability and real-time performance of the combat mission planning simulation system.

[0057] In some embodiments of the present invention, a behavior modeling method of a behavior tree is adopted to logically configure the constructed second rule instance adapted to a specific combat scenario, including: defining the structure of the behavior tree, configuring the control node, condition node, action node, and connection node of the rule in the structure of the behavior tree, and configuring the logic between each node to obtain a combat rule adapted to a specific combat scenario. Specifically, during implementation, first, according to the requirements of the combat scenario, design the hierarchical structure of the behavior tree, select an appropriate type of control node (such as a sequence node, a selection node, a parallel node), configure the condition node according to the condition part of the rule instance, configure the action node according to the response part of the rule instance, and finally connect the control node, condition node, and action node according to the logical relationship to obtain a combat rule adapted to a specific combat scenario. Adopting the behavior modeling method of a behavior tree can efficiently and flexibly configure the rule logic to adapt to complex combat scenarios and task requirements.

[0058] In some embodiments of the present invention, the method further includes: generating a rule version for the reconfigured combat rule adapted to a specific combat scenario, which is used to record the change information of the rule, and the change information includes the change time, the person making the change, and the change content. The embodiments of the present invention introduce a rule version management mechanism into the system. When the user edits or expands the rule, the system automatically generates a new rule version. Each version records detailed change information, including the change time, the person making the change, the change content, etc. Specifically, when the user adjusts the rule parameters for coping with enemy air raids, the system records the time of this adjustment, the name of the operator, and the change content, etc. In this way, when it is necessary to trace back or compare different rule versions later, the change process of the rule can be clearly understood, which is convenient to select the appropriate rule version according to the combat requirements. At the same time, a backup function can be provided for important rule versions to prevent the loss of rules due to misoperation or system failure. When the system is upgraded or a large-scale rule adjustment is carried out, the existing rule versions can be backed up first. If problems occur after the upgrade or adjustment, it can be quickly restored to the previous stable rule version.

[0059] Such as Figure 2As shown in the figure, a scalable combat mission planning simulation system 200 according to the first embodiment of the present invention includes:

[0060] A rule parameter configuration module 201, configured to define a rule template in a combat mission planning system, configure rule parameters in the rule template, and generate a specific first rule instance according to the configured parameter values; wherein, the rule template includes a rule name, a rule description, a rule parameter list, and a logical relationship, and the rule parameters include battlefield environment condition parameters, combat unit status parameters, and tactical response parameters;

[0061] A rule decomposition and construction module 202, configured to decompose the first rule instance into multiple element components according to specific functions, and combine the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein, the element components include condition element components, status element components, and response element components;

[0062] A rule logic configuration module 203, configured to perform logical configuration on the second rule instance adapted to a specific combat scenario constructed by using a behavior modeling method of a behavior tree to obtain a combat rule adapted to a specific combat scenario.

[0063] In specific implementation, after constructing a rule instance adapted to a specific combat scenario, the rule decomposition and construction module 202 is further configured to: detect conflicts in the condition part and the response part of multiple rules, and if there are rule conflicts, calculate the priorities of the conflicting rules respectively, and determine the execution order of the conflicting rules according to the priorities; wherein, the detection of the condition part includes numerical range conflict detection and logical relationship conflict detection, and the detection of the response part includes resource competition conflict detection and action order conflict detection.

[0064] As Figure 3 shown, in the second embodiment of the present invention, the system further includes a rule version management module 204, configured to generate a rule version for the rule adapted to a specific combat scenario after reconfiguration, and record the change information of the rule, where the change information includes the change time, the change personnel, and the change content.

[0065] Through rule parameterized modeling in the embodiments of the present invention, users can quickly adjust rule parameters according to real-time battlefield intelligence, enabling the system to adapt to different combat scenarios and providing timely and effective decision support for combat command. By combining componentized modeling and behavior tree behavior modeling, it is convenient for users to add, delete, or modify rule components, realizing dynamic expansion of rules, enabling the system to more accurately simulate complex battlefield environments and combat behaviors, and improving the accuracy and reliability of simulation results.

[0066] In one embodiment, a computer device is provided, as Figure 4As shown, it includes a memory 301, a processor 302, and a computer program stored on the memory 301 and executable on the processor 302. When the processor 302 executes the computer program, it implements the above-mentioned scalable combat mission planning simulation method.

[0067] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0068] In this embodiment, a computer-readable storage medium is provided, and the computer-readable storage medium stores a computer program for executing the above-mentioned scalable combat mission planning simulation method.

[0069] Specifically, the computer-readable storage medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette tapes, magnetic disk storage, or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. As defined herein, computer-readable storage media do not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0070] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the embodiments of the present invention can be implemented by a general-purpose computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. Optionally, they can be implemented by program codes executable by the computing device, so that they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately fabricated into individual integrated circuit modules, or multiple modules or steps among them can be fabricated into a single integrated circuit module to be implemented. Thus, the embodiments of the present invention are not limited to any specific combination of hardware and software.

[0071] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A scalable combat mission planning simulation method, characterized in that: include: A rule template is defined in a combat mission planning system, rule parameters are configured in the rule template, and a specific first rule instance is generated according to the configured parameter values; wherein the rule template includes a rule name, a rule description, a rule parameter list and a logical relationship, and the rule parameters include a battlefield environment condition parameter, a combat unit state parameter and a tactical response parameter; Decomposing the first rule instance into a plurality of element components according to specific functions, and combining the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein the element components include a condition element component, a state element component, and a response element component; Using a behavior tree behavior modeling method, logically configuring the constructed second rule instance adapted to the specific combat scenario, to obtain a combat rule adapted to the specific combat scenario; After constructing a second rule instance that is adapted to a specific combat scenario, it also includes: Perform conflict detection on the condition parts and response parts in multiple rule instances. If there is a rule conflict, calculate the priorities of the conflicting rules respectively, and determine the execution order of the conflicting rule instances according to the priorities; wherein the detection of the condition part includes value range conflict detection and logical relationship conflict detection, and the detection of the response part includes resource competition conflict detection and action sequence conflict detection; The priority calculation formula of the rule is as follows: Where P is the priority score of the rule, W i is the weight of the i-th parameter in the rule, indicating the influence of the parameter on the priority of the rule. i is the state value of the i-th parameter, indicating the specific value or score of the parameter in the current battlefield environment, n is the total number of parameters in the rule, T is the time decay factor, indicating the time sensitivity of the rule, M is the task target matching degree, indicating the degree of fit between the rule and the current combat task target, α, β, γ are the weight coefficients of each dimension, satisfying α+β+γ=1; The method processes rule conflicts through conflict detection algorithms and priority calculations, wherein an interval comparison algorithm is used for value range conflict detection, and Boolean logic reasoning is used for logical relationship conflict detection; The resource contention conflict detection process includes: Establishing a resource allocation table, recording status information of each resource in the resource allocation table, wherein the status information includes the current usage status of each resource, the corresponding allocation rule and the allocation quantity information; Constructing a conflict matrix using different rules as rows and columns respectively, traversing the conflict matrix, judging according to the resource allocation table, determining whether there is a conflict between two rules in using the same resource, and if there is a conflict, marking the corresponding position of the matrix; Periodically or when the rules are updated, traverse the conflict matrix and detect the conflict markers in the conflict matrix; The process of action sequence conflict detection includes: Number each combat action in the same combat scenario and define the dependencies between the combat actions; Construct an action sequence by arranging the combat actions involved in each rule according to their interdependencies and corresponding numbering order; The action sequences of different rules are detected to determine whether the action sequences of different rules are consistent with the predefined action dependency graph. If not, it is determined that there is an action sequence conflict.

2. The scalable combat mission planning simulation method according to claim 1, characterized in that: The behavior tree behavior modeling method is used to logically configure the constructed second rule instance adapted to the specific combat scenario, including: Define the structure of the behavior tree, configure the control nodes, condition nodes, action nodes, and connection nodes of the rules in the structure of the behavior tree, and configure the logic between the nodes to obtain combat rules that adapt to specific combat scenarios.

3. The scalable combat mission planning simulation method according to claim 2, characterized in that: The method further comprises: A rule version is generated for the reconfigured combat rules adapted to the specific combat scenario, which is used to record the change information of the rules, and the change information includes the change time, the change personnel and the change content.

4. An extensible combat mission planning simulation system using the extensible combat mission planning simulation method according to claim 1, characterized in that: include: A rule parameter configuration module, used to define a rule template in the combat mission planning system, configure rule parameters in the rule template, and generate a specific first rule instance according to the configured parameter values; wherein the rule template includes a rule name, a rule description, a rule parameter list and a logical relationship, and the rule parameters include battlefield environment condition parameters, combat unit status parameters and tactical response parameters; A rule decomposition and construction module, used to decompose the first rule instance into multiple element components according to specific functions, and combine the element components according to different combat scenarios to construct a second rule instance adapted to a specific combat scenario; wherein the element components include condition element components, state element components and response element components; The rule logic configuration module is used to adopt the behavior modeling method of the behavior tree to logically configure the constructed second rule instance adapted to the specific combat scenario, so as to obtain the combat rules adapted to the specific combat scenario.

5. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the scalable combat mission planning simulation method described in any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing the scalable combat mission planning simulation method according to any one of claims 1 to 3.

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