Extensible combat mission planning simulation method, system, equipment and medium

Abstract

The invention provides an extensible combat mission planning simulation method, system, device and medium, and relates to the technical field of computer combat simulation, the method comprises the following steps: 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 a plurality of element components according to a specific function, and combining the element components according to different combat scenes to construct a second rule instance adapted to the specific combat scene; and performing logic configuration on the constructed second rule instance adapting to the specific combat scene by adopting a behavior modeling method of a behavior tree to obtain a combat rule adapting to the specific combat scene. According to the invention, by providing a convenient rule editing and expanding mode, the editability and expandability of the rule are realized, the adaptability of the system to diversified combat scenes is improved, and more powerful support is provided for combat command decisions.

Description

Technical Field

[0001] The present invention relates to the technical field of computer combat simulation, and in particular to an expandable combat mission planning simulation method, system, equipment and medium. Background Art

[0002] In the planning of combat missions at the system level, battlefield elements are extremely complex. From the perspective of the geographical environment, it covers different terrains such as mountains, plains, and waters. Each terrain has different effects on combat operations. For example, mountains affect the mobility of troops and the quality of communication signal transmission, while waters limit the range of action of land equipment. In terms of military power, it involves multi-domain combat forces such as land, sea, air, space, and electricity, and the coordination relationship between various forces is complex. At the same time, the battlefield space changes in a complex manner. During the operation, the combat area may expand or shrink rapidly, and the focus of the operation will also shift rapidly.

[0003] There are many problems in the model construction of the existing combat mission planning system. On the one hand, due to the complex changes in the battlefield space that need to be dealt with, it is extremely difficult to judge various situations in the experiment and design corresponding disposal rules. For example, when facing the sudden electronic interference launched by the enemy, the system needs to quickly judge the type, intensity, range and other situations of the interference, and make disposal decisions such as switching communication frequency bands and enabling backup communication links according to the corresponding rules. This process involves a lot of complex judgment logic and disposal rule design. On the other hand, the relevant software design and data are often customized for specific applications. If the user's customizable and scalable capabilities are not fully considered during the system design, 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 the rules and expand functions, and it is difficult to adapt to diversified combat needs.

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

[0005] In view of this, an embodiment of the present application provides an extensible combat mission planning simulation system, which realizes the editability and extensibility of rules by providing convenient rule editing and expansion methods, improves the system's adaptability to diverse combat scenarios, and provides stronger support for combat command decisions.

[0006] The embodiment of the present application provides the following technical solution: an extensible combat mission planning simulation method, comprising: 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; The behavior modeling method of the behavior tree is adopted to logically configure the constructed second rule instance adapted to the specific combat scenario to obtain the combat rules adapted to the specific combat scenario.

[0007] According to an embodiment of the present application, after constructing the second rule instance adapted to a specific combat scenario, the following steps are further included: Conflict detection is performed on the condition parts and response parts in multiple rule instances. If there is a rule conflict, the priorities of the conflicting rules are calculated respectively, and the execution order of the conflicting rule instances is determined 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.

[0008] According to an embodiment of the present application, the priority calculation formula of the rule is as follows:

[0009] 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 ith 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, respectively, satisfying α+β+γ=1.

[0010] According to an embodiment of the present application, the process of detecting resource contention conflicts 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, the conflict matrix is ​​traversed to detect the conflict marks in the conflict matrix.

[0011] According to an embodiment of the present application, the process of detecting conflict in action sequence 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.

[0012] According to an embodiment of the present application, a behavior modeling method of a behavior tree is used to logically configure the constructed second rule instance adapted to a 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.

[0013] According to an embodiment of the present application, the method further includes: 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.

[0014] The present application also provides an expandable combat mission planning simulation system, comprising: 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.

[0015] The present application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned scalable combat mission planning simulation method when executing the computer program.

[0016] The present application also provides a computer-readable storage medium, which stores a computer program for executing the above-mentioned scalable combat mission planning simulation method.

[0017] Compared with the prior art, the beneficial effects achieved by at least one of the above technical solutions adopted in the embodiments of this specification include at least the following: The embodiments of the present invention use rule parameterized modeling to enable users to quickly adjust rule parameters based on real-time battlefield intelligence, so that the system can adapt to different combat scenarios and provide timely and effective decision support for combat command. By combining componentized modeling with behavior tree behavior modeling, it is convenient for users to add, delete or modify rule components, realize dynamic expansion of rules, enable the system to more accurately simulate complex battlefield environments and combat behaviors, and improve the accuracy and reliability of simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a schematic diagram of a flow chart of an expandable combat mission planning simulation method according to an embodiment of the present invention; Figure 2 It is a schematic diagram of the structure of an expandable combat mission planning simulation system according to the first embodiment of the present invention; Figure 3 2 is a schematic diagram of the structure of an expandable combat mission planning simulation system according to a second embodiment of the present invention; Figure 4 It is a structural schematic diagram of the computer device of the present invention. DETAILED DESCRIPTION

[0020] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0021] The following describes the implementation methods of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents 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 methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the following embodiments and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0022] like Figure 1 As shown, an embodiment of the present invention provides an extensible combat mission planning simulation method, including: 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 a battlefield environment condition parameter, a combat unit state parameter and a tactical response parameter; 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 a condition element component, a state element component, and a response element component; S103. Using a behavior tree behavior modeling method, logically configure the constructed second rule instance adapted to the specific combat scenario to obtain combat rules adapted to the specific combat scenario.

[0023] The embodiment of the present invention realizes the editability and extensibility of combat simulation system rules by introducing parametric modeling, componentization technology and behavior tree modeling method. Rule parameters can be flexibly configured according to specific needs to adapt to different simulation scenarios; through parametric modeling, the system can easily expand new rule templates and parameters. Through componentization modeling technology, rule components can be easily added, deleted or modified to achieve dynamic expansion of rules. Through parametric modeling and componentization technology, the system can more accurately simulate complex battlefield environments and combat behaviors, and improve the reliability of simulation results.

[0024] In the specific implementation, in S101, the parametric modeling technology of the rule model is used to first define the rule template in the system. The rule template includes the rule name, rule description, parameter list and logical relationship, etc. The key factors in the rule are extracted as parameters for configuration to generate specific rule instances. For example, in the rules for judging the degree of enemy air strike threat, key factors such as the number of enemy fighters, flight speed, and weapon mounting type are set as parameters. In the system application stage, the rules can be instantiated and customized by configuring these rule parameters according to the actual combat scenario. For example, in different combat areas, the enemy's air force deployment is different. According to intelligence information, the number of enemy fighters and other parameters can be adjusted to make the rules more suitable for the current combat situation, so as to accurately judge the degree of air strike threat.

[0025] In the specific implementation, in S102, the component modeling technology is used to split the rules into more fine-grained conditions, states, responses and other elements. Different rule components are combined into a complete rule by dragging, combining, etc. Each component is responsible for a specific function, and components can be added, deleted or modified as needed. Specifically, taking the rules for responding to the attack of enemy ground forces as an example, the conditional elements may include the attack direction, force size, equipment type, etc. of the enemy forces; the state elements may involve the firmness of our defensive positions, the state of our defensive forces, etc.; the response elements include our counterattack strategies, force deployment plans, etc. By combining these different elements, rules that adapt to specific combat scenarios can be constructed. When the combat scenario changes, the combination of various elements can be flexibly adjusted to quickly generate new rules. For example, if the enemy changes the direction of attack, the attack direction parameters in the conditional elements can be adjusted, and the force deployment strategy in the response elements can be adjusted accordingly to construct new response rules.

[0026] In some embodiments of the present invention, after constructing the second rule instance adapted to a specific combat scenario, the method further includes: Conflict detection is performed on the condition parts and response parts in multiple rule instances. If there is a rule conflict, the priorities of the conflicting rules are calculated respectively, and the execution order of the conflicting rule instances is determined 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.

[0027] When multiple rules are generated and when multiple rules meet the trigger conditions at the same time, conflicts may occur, causing the system to be unable to determine which rule to execute. In order to solve this problem, an embodiment of the present invention proposes a rule conflict detection and solution, which ensures that the system can handle rule conflicts efficiently and reasonably through a conflict detection algorithm and priority calculation. In specific implementation, rule conflicts are mainly divided into the following two categories: 1. Condition conflict: The conditions of multiple rules partially overlap or are completely consistent, resulting in the trigger conditions being met at the same time. 2. Response conflict: There are contradictions in the response parts of multiple rules.

[0028] The conditional conflicts include 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. In specific implementation, all rules involving numerical range conditions are traversed, and the numerical range conditions in each rule, such as (a1, b1), are compared with the similar numerical range conditions (a2, b2) in other rules. If there is an overlap in the numerical range, it is considered that there is a numerical range conflict. (2) Logical relationship conflict detection: The conditions in the rules may also have logical conflicts, which can be specifically detected using Boolean logic reasoning; for example, the conditions in the rules are parsed by logical expressions, the conditions described in natural language are converted into Boolean logic expressions, and logical reasoning rules are used to check whether the logical expressions have contradictory expressions.

[0029] The response conflict includes 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, such as multiple rules competing for limited ammunition resources or communication channel resources at the same time. In specific 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, and the status information includes the current usage status of each resource, the corresponding allocation rule, and the allocation quantity information; constructing a conflict matrix with different rules as rows and columns, traversing the conflict matrix, judging according to the resource allocation table, determining whether there is a conflict between the two rules in the use of the same resource, and if there is a conflict, marking the corresponding position of the matrix; regularly or when the rules are updated, traversing the conflict matrix, and detecting the conflict marks in the conflict matrix. (2) Action sequence conflict detection: Combat operations have certain sequence requirements, and multiple rules may conflict in the order of combat operations. In specific 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 and A2, and defining the dependency relationship between the combat actions, such as A2 depends on A1, that is, A1→A2; constructing an action sequence according to the mutual dependency relationship and the corresponding numbering order of the combat actions involved in each rule; 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 not, it is determined that there is an action sequence conflict.

[0030] The embodiment of the present invention solves the rule conflict problem based on priority. The priority calculation formula of the rule is as follows:

[0031] Where 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. The parameter can be set based on experience or learned from historical data through machine learning algorithms; S 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, and the priority gradually decreases over time; the time decay factor T can be calculated by the formula, , λ is the decay coefficient, which is used to control the speed of priority decay over time, and t is the time interval from the creation of the rule to the current moment. M is the task target matching degree, which indicates the degree of fit between the rule and the current combat task target. The higher the matching degree, the higher the priority, which can be obtained by the ratio of the number of matching parameters between the rule and the task target to the total number of parameters of the task target; α, β, and γ are the weight coefficients of each dimension, respectively, satisfying α+β+γ=1.

[0032] The embodiments of the present invention can reduce the computational complexity while ensuring the accuracy of priority calculation, thereby improving the practicality and real-time performance of the combat mission planning simulation system.

[0033] In some embodiments of the present invention, a behavior modeling method of a behavior tree is used 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. In specific implementation, firstly, according to the requirements of the combat scenario, a hierarchical structure of the behavior tree is designed, and an appropriate control node type (such as a sequence node, a selection node, and a parallel node) is selected. According to the condition part of the rule instance, a condition node is configured, and according to the response part of the rule instance, an action node is configured. Finally, the control node, the condition node and the action node are connected according to a logical relationship to obtain a combat rule adapted to a specific combat scenario. The behavior modeling method of the behavior tree can efficiently and flexibly configure the rule logic to adapt to complex combat scenarios and task requirements.

[0034] In some embodiments of the present invention, the method further includes: generating a rule version for the reconfigured combat rules adapted to a specific combat scenario, and recording the change information of the rules, wherein the change information includes the change time, the change personnel, and the change content. The embodiment of the present invention introduces a rule version management mechanism in 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 change personnel, the change content, etc. In specific implementation, if the user adjusts the rule parameters for dealing with enemy air strikes, the system records the time of the adjustment and the name of the operator, as well as the change content, etc. In this way, when it is necessary to trace back or compare different rule versions in the future, the change process of the rules can be clearly understood, and it is convenient to select the appropriate rule version according to combat needs. 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 large-scale rule adjustments are made, the existing rule version can be backed up first. If problems occur after the upgrade or adjustment, the previous stable rule version can be quickly restored.

[0035] like Figure 2As shown, an expandable combat mission planning simulation system 200 according to the first embodiment of the present invention includes: A rule parameter configuration module 201 is 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 202 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 condition element components, state element components and response element components; The rule logic configuration module 203 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.

[0036] In specific implementation, after constructing a rule instance that adapts to a specific combat scenario, the rule decomposition and construction module 202 is also used to: perform conflict detection on the conditional part and the response part in multiple rules. If there is a rule conflict, the priorities of the conflicting rules are calculated respectively, and the execution order of the conflicting rules is determined according to the priorities; wherein the detection of the conditional 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.

[0037] like Figure 3 As shown, in the second embodiment of the present invention, the system also includes a rule version management module 204, which is used to generate a rule version for the reconfigured rules adapted to the specific combat scenario, and is used to record rule change information, wherein the change information includes change time, change personnel and change content.

[0038] The embodiment of the present invention uses parameterized rule modeling to enable users to quickly adjust rule parameters based on real-time battlefield intelligence, so that the system can adapt to different combat scenarios and provide timely and effective decision support for combat command. By combining componentized modeling with behavior tree behavior modeling, it is convenient for users to add, delete or modify rule components, realize dynamic expansion of rules, enable the system to more accurately simulate complex battlefield environments and combat behaviors, and improve the accuracy and reliability of simulation results.

[0039] In one embodiment, a computer device is provided, such as Figure 4As shown, it includes a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the computer program, the above-mentioned scalable combat mission planning simulation method is implemented.

[0040] Specifically, the computer device may be a computer terminal, a server or a similar computing device.

[0041] In this embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program for executing the above-mentioned scalable combat mission planning simulation method.

[0042] Specifically, computer-readable storage media include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. 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 technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable storage media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0043] Obviously, those skilled in the art should understand that the modules or steps of the above-mentioned embodiments of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a 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 from that here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the embodiments of the present invention are not limited to any specific combination of hardware and software.

[0044] The above is only a specific implementation 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 a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on 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; The behavior modeling method of the behavior tree is adopted to logically configure the constructed second rule instance adapted to the specific combat scenario to obtain the combat rules adapted to the specific combat scenario.

2. The scalable combat mission planning simulation method according to claim 1, characterized in that: After constructing a second rule instance that is adapted to a specific combat scenario, it also includes: Conflict detection is performed on the condition parts and response parts in multiple rule instances. If there is a rule conflict, the priorities of the conflicting rules are calculated respectively, and the execution order of the conflicting rule instances is determined 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.

3. The scalable combat mission planning simulation method according to claim 2, characterized in that: 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 ith 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, respectively, satisfying α+β+γ=1.

4. The scalable combat mission planning simulation method according to claim 2, characterized in that: 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, the conflict matrix is ​​traversed to detect the conflict marks in the conflict matrix.

5. The scalable combat mission planning simulation method according to claim 2, characterized in that: 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.

6. 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.

7. The scalable combat mission planning simulation method according to claim 6, 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.

8. An extensible combat mission planning simulation system, 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.

9. 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 7 is implemented.

10. 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 7.

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