Metamodel-based behavior center simulation model construction method

Abstract

A behavior center simulation model construction method based on a meta-model comprises the steps that a micro-behavior meta-model is constructed, the micro-behavior meta-model comprises control class meta-model elements and function class meta-model elements, and the micro-behavior meta-model is constructed based on the function class meta-model elements and the control class meta-model elements in the micro-behavior meta-model; a microscopic behavior model comprising three behavior levels is constructed, and a simulation model with the microscopic behavior model as the center is constructed. According to the method, behaviors in a functional component are decoupled from an entity model, a meta-model technology is applied, full-behavior space modeling is carried out in a low-code form, the behavior modeling efficiency is improved, meanwhile, functions and control of the behaviors are decoupled in a behavior structure, modeling of behaviors of any granularity and combinations of behaviors of different granularities can be supported technically, and the behavior modeling efficiency is improved. The reusability of different levels of behaviors in the simulation model is solved, and the development efficiency of the simulation model is also improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and particularly to a method for constructing a behavior-centered simulation model based on a meta-model. Background Art

[0002] When using simulation methods to analyze complex problems, it is usually necessary to construct a large number of simulation models that are interdisciplinary and cross-domain. Traditional modeling techniques usually use inheritance and composition methods to construct a simulation model framework, and use the simulation model framework to carry out the reuse of existing models in the field and the joint development of new models, so as to improve the modeling efficiency.

[0003] The simulation model framework based on inheritance and composition belongs to an entity-centered model framework, which is mainly reflected in two aspects: one is the modeling process, where the entity model is constructed first, then the behavior model is constructed, and finally the entity behavior association relationship is set; the other is the model structure, which is organized around the entity model. The entity model provides simple behaviors by integrating functional components and provides more complex behaviors by integrating behavior models. This entity-centered model framework has two problems: one is the low development efficiency of simple behaviors, and the other is the uneven levels of simple behaviors. The above two problems restrict the reusability of the simulation model at different levels and also reduce the development efficiency of the simulation model. Summary of the Invention

[0004] Based on this, it is necessary to provide a method for constructing a behavior-centered simulation model based on a meta-model for the above technical problems.

[0005] According to the first aspect of this application, a method for constructing a behavior-centered simulation model based on a meta-model is proposed. The method includes: Construct a micro-behavior meta-model; the micro-behavior refers to the behavior that constructs the association of the smallest identifiable entities at the micro level of a complex system; the micro-behavior meta-model includes control-type meta-model elements and function-type meta-model elements; Based on the function-type meta-model elements and control-type meta-model elements in the micro-behavior meta-model, construct a micro-behavior model including three behavior levels; Construct a simulation model centered on the micro-behavior model.

[0006] In one embodiment, the control-type meta-model elements include six control-type meta-model elements: start, end, sequence, parallel, selection, and convergence.

[0007] In one embodiment, the function-type meta-model elements include two types of function-type meta-model elements: general function-type meta-model elements and special function-type meta-model elements.

[0008] In one embodiment, the general function class meta-model element specifies the loading, input, output, and call interfaces of the general function, and is formally described as: ; Wherein, represents the set of function model interfaces specified by the general function class meta-model element, represents the loading interface, which, when used, realizes the dynamic loading of the component dynamic library into the memory; represents the input interface. Each time the function component is used, this interface needs to be called first to assign values to the function calculation parameters; represents the call interface. After calling the input interface, this interface is called to specify the specific function in the dynamic library to be called, which is used for function calculation to generate the required output; represents the output interface. After each use of the function component, the output result of the function calculation is obtained by calling this interface.

[0009] In one embodiment, the special function class meta-model element includes six elements: loading function, assembly behavior, entity generation, entity cancellation, model output, and model interaction; Formally described as: ; Wherein, represents the loading function, that is, loading a special function model component from the model library; represents the assembly behavior, that is, loading a behavior from the model library and combining it with the behavior being edited; represents entity generation, that is, creating an entity of a specified type and assigning initial parameters to it; represents entity destruction, that is, canceling a specified entity from the simulation engine to make it exit the simulation; represents model output, that is, outputting the latest state of this entity and the events generated by key state changes; represents model interaction, that is, the information interaction that this entity needs to perform with other entities or other components within the entity.

[0010] In one embodiment, based on the function class meta-model element and the control class meta-model element in the micro-behavior meta-model, a micro-behavior model including three behavior levels is constructed, including: The simulation behavior is divided into function-level behavior, action-level behavior, and task-level behavior; among them, the function-level behavior refers to the general function or the special function, the action-level behavior refers to the minimum distinguishable behavior ability provided by a specific entity, and the task-level behavior refers to the behavior that can complete an independent business ability. Develop a dedicated function model based on the dedicated function class meta-model elements, and the dedicated function corresponding to the dedicated function model exists in the form of a loadable dynamic library; Based on the control class meta-model elements, the dedicated function model, and the general function class meta-model elements, construct two types of hierarchical behaviors: action-level behavior and task-level behavior in the form of a tree structure.

[0011] In one implementation, the method further includes: Run the micro-behavior model based on the hierarchical finite state machine.

[0012] In one implementation, the hierarchical finite state machine includes an upper-layer behavior logic control state machine and a lower-layer function state machine; The running of the micro-behavior model based on the hierarchical finite state machine includes: The upper-layer behavior logic control state machine is used to parse the behavior logic of the micro-behavior model and issue function running instructions to the lower-layer state machine according to the behavior logic sequence; The lower-layer function state machine is used to load the general function class meta-model elements or the dedicated function model according to the control instructions issued by the upper-layer behavior logic control state machine and execute the specified behavior.

[0013] In one implementation, the simulation model centered on the micro-behavior model includes the following components: Logic control state machine, function state machine, behavior container, entity container, function container, component manager, shared blackboard, behavior interaction, behavior output, behavior input, the micro-behavior meta-model, and behavior data; among them, the behavior container is at least used to load the logic control state machine; the function container is at least used to load the function state machine; the behavior data includes the micro-behavior model and the dedicated function model dynamic library.

[0014] According to the second aspect of the present application, the present application provides a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in the above first aspect are implemented.

[0015] Based on the above-provided method for constructing a behavior-centered model based on a meta-model, decouple the behavior in the functional component from the entity model, use the meta-model technology to model the entire behavior space in a low-code form, which improves the behavior modeling efficiency. At the same time, decouple the behavior running environment and the behavior description in the behavior structure, and decouple the function and control of the behavior, which can technically support the modeling of behaviors at any granularity and the combination of behaviors at different granularities, solve the reusability of different levels of behaviors in the simulation model, and also improve the simulation model development efficiency. Description of the Drawings

[0016] Figure 1 It is a schematic flowchart of a method for constructing a behavior-centered simulation model based on a meta-model provided in an embodiment; Figure 2 It is a schematic diagram of a microscopic behavior model in json format provided in an embodiment; Figure 3 It is a schematic structural diagram of a device for constructing a behavior-centered simulation model based on a meta-model provided in an embodiment; Figure 4 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0017] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] The simulation model framework based on inheritance and composition belongs to the entity-centered model framework, which is mainly reflected in two aspects: one is the modeling process, where the entity model is constructed first, then the behavior model is constructed, and finally the entity behavior association relationship is set; the other is the model structure, which is organized around the entity model. The entity model provides simple behaviors through integrating functional components and provides more complex behaviors through integrating behavior models. There are two problems with this entity-centered model framework: one is the low development efficiency of simple behaviors. The framework only provides low-code and no-code development support capabilities for complex behavior models such as behavior trees, state machines, and workflows, but for the simple behaviors coupled in the functional components, full-scale code development is required for initial development or subsequent adjustment, and common functions such as visibility calculation (used by both the communication and detection functional components) have low reuse efficiency, which restricts the model development efficiency; the other is that the levels of simple behaviors are uneven. For example, in a certain commercial simulation system, the functional components include behaviors such as returning to the airport, turning on the sensor, and maneuvering towards the target point. The modeling granularities of these three behaviors are not at the same level. The modeling granularity of returning to the airport is the collaborative actions of people and airplanes, the modeling granularity of turning on the sensor is a power-on button provided by the device, and the modeling granularity of maneuvering towards the target point is between the two. This non-uniformity of behavior levels restricts the cross-simulation platform reuse of entity models and behavior models. The above two problems restrict the reusability of the simulation model and reduce the simulation model development efficiency from different levels.

[0019] To address the above problems, the present invention provides a method for constructing a behavior-centered model based on a meta-model. The behavior-centered aspect is reflected in three aspects. First, in the modeling process, behaviors are constructed first, and then entities are constructed. Second, in the model structure, the model structure is organized around behaviors. The behaviors in the functional components are decoupled from the entity model, and the meta-model technology is used to model the entire behavior space in a low-code form, improving the efficiency of behavior modeling. Third, in the behavior structure, the behavior running environment and the behavior description are decoupled. Different levels of behavior running are achieved through a hierarchical finite state machine. The functions and controls of behaviors are decoupled, which technically supports the modeling of behaviors at any granularity and the combination of behaviors at different granularities, solving the problem of difficult reuse of behaviors at different levels.

[0020] Specifically, as Figure 1 shown, a method for constructing a behavior-centered model based on a meta-model includes: S101, constructing a micro-behavior meta-model; the micro-behavior refers to the behavior associated with the microscopically smallest identifiable entities in a complex system; the micro-behavior meta-model includes control-class meta-model elements and function-class meta-model elements; S102, based on the function-class meta-model elements and control-class meta-model elements in the micro-behavior meta-model, constructing a micro-behavior model including three behavior levels; S103, constructing a simulation model centered on the micro-behavior model.

[0021] The following introduces the micro-behavior meta-model in S101 above.

[0022] The micro-behavior refers to the behavior associated with the microscopically smallest identifiable entities in a complex system. The micro-behavior meta-model includes control-class meta-model elements and function-class meta-model elements. The formal description is as follows: ; Among them, represents the micro-behavior meta-model, represents the control-class meta-model elements, represents the function-class meta-model elements.

[0023] The control-class meta-model elements include start, end, sequence, parallel, selection, and convergence, six control-class meta-model elements. The formal description is as follows: ; Among them, represents the start meta-model, that is, the start of a behavior logic or sub-behavior logic. End represents the end meta-model, that is, the end of a behavior logic or sub-behavior logic. represents the sequence meta-model, that is, the relationship between the pre-behavior and the post-behavior is one-to-one, and the execution logic is to execute the pre-behavior first and then the post-behavior. Represents a parallel metamodel, that is, there is a one-to-many relationship between the pre-behavior and the post-behaviors. The execution logic is to first execute the pre-behavior and then simultaneously execute multiple parallel post-behaviors. Represents a selection metamodel, that is, there is a one-to-many relationship between the pre-behavior and the post-behaviors. The execution logic is a restrictive pre-behavior, and then, according to the state value, select one of the multiple post-behaviors to execute. Represents a convergence metamodel, indicating that the pre-behavior and the post-behavior are in a many-to-one relationship. The execution logic is to execute the post-behavior after the pre-behavior is completed.

[0024] The functional class metamodel elements include general and special functional class metamodel elements, and the formal description is as follows: ; Among them, Represents a special functional metamodel element. Represents a general functional metamodel element.

[0025] The general functional class metamodel elements specify the loading, input, output, and call interfaces of the general function, and the formal description is as follows: ; Among them, Represents the set of function model interfaces specified by the general functional class metamodel elements; Represents the loading interface. When this interface is used, it realizes the loading of the component dynamic library into the memory; among them, the general function model components are predefined in the component dynamic library, such as the through-view calculation equation, the radar equation, the six-degree-of-freedom kinematic equation, etc.

[0026] Represents the input interface. Each time this function component is used, this interface needs to be called first to assign values to the function calculation parameters; Represents the call interface. After calling the input interface, this interface is called to specify the specific function in the dynamic library to be called for function calculation to generate the required output; Represents the output interface. After each use of the function component, the output result of the function calculation is obtained by calling this interface.

[0027] The special functional class metamodel elements include six elements: loading function, assembling behavior, generating entity, canceling entity, model output, and model interaction; The formal description is as follows: ; Among them, Represents the loading function, that is, loading a special function model component from the model library; Represents the assembly behavior, that is, loading a behavior from the model library and combining it with the behavior being edited; Represents entity generation, that is, creating an entity of a specified type and assigning initial parameters to it; Represents entity destruction, that is, unregistering a specified entity from the simulation engine to let it exit the simulation; Represents model output, that is, outputting the latest state of this entity and the events generated by key state changes; Represents model interaction, that is, the information interaction that this entity needs to perform with other entities or other components within the entity.

[0028] After constructing the above-mentioned micro-behavior meta-model including functional meta-model elements and control meta-model elements, a micro-behavior model including three behavior levels can be constructed based on the micro-behavior meta-model.

[0029] Specifically, the above S102 can be implemented in the following way.

[0030] Divide the simulation behavior into functional-level behavior, action-level behavior, and task-level behavior; among them, functional-level behavior refers to general functions or special functions, action-level behavior refers to the minimum distinguishable behavior ability provided by a specific entity, and task-level behavior refers to the behavior that can complete independent business capabilities; Develop a special function model based on the special function class meta-model elements, and the special function corresponding to the special function model exists in the form of a loadable dynamic library; Based on the control class meta-model elements, special function model, and general function class meta-model elements, construct two types of behavior at the action level and task level in the form of a tree structure.

[0031] Specifically, divide the simulation behavior into functional-level behavior, action-level behavior, and task-level behavior, and formally describe it as: ; Among them, Represents the behavior level set, Represents functional-level behavior, referring to the behavior implemented by general function class meta-model elements, such as line-of-sight calculation, radar equation, six-degree-of-freedom maneuver, etc., Represents action-level behavior, that is, the minimum distinguishable behavior ability provided by a specific entity, such as sensor area search, aircraft cruising in the air, etc., Represents task-level behavior, that is, the behavior that can complete independent business capabilities, usually implemented by combining control class meta-model elements, function class meta-model elements, and functional-level behavior as needed, such as air material transportation, facility and equipment maintenance, etc.

[0032] When developing a dedicated function model based on the dedicated function class meta-model elements, the simulation modeling user can develop a dedicated function model based on the interface requirements of the dedicated function meta-model and form a loadable dynamic library.

[0033] When constructing two types of hierarchical behaviors, namely action-level behavior and task-level behavior, based on the control class meta-model elements, dedicated function models, and general function class meta-model elements, the constructed two-layer behavior is described using a tree structure. The constructed tree-structured behavior model is stored in the database in JSON format, as specifically Figure 2 shown, for the subsequent construction and operation of the simulation model.

[0034] After constructing the micro-behavior model, the micro-behavior model can be run. Specifically, this application proposes to run the micro-behavior model based on a hierarchical finite state machine to achieve the decoupling of the function and control of the behavior. Among them, the hierarchical finite state machine includes an upper-layer behavior logic control state machine and a lower-layer function state machine; the upper-layer behavior logic control state machine is embedded in the behavior container to parse the behavior logic of the micro-behavior model and issue function operation instructions to the lower-layer state machine according to the order of the behavior logic; The lower-layer function state machine is embedded in the function container to load general function class meta-model elements or dedicated function models according to the control instructions issued by the upper-layer behavior logic control state machine and execute the specified behavior.

[0035] The logic control state machine and the function state machine have a one-to-many relationship, that is, one logic control state machine can control the operation of multiple function state machines. The logic control state machine manages the function state machines by querying the model structure data in the entity container and issues function operation instructions to the function state machines through the interaction blackboard. The function state exists in the form of components, supporting one function to build one component, or several related functions to build one component. The function state machine loads and calls function functions according to the interfaces specified by the function meta-model to obtain the output.

[0036] In the above S103, after constructing the micro-behavior model, a simulation model centered on the micro-behavior model can be constructed. The simulation model includes: A logic control state machine, a function state machine, a behavior container, an entity container, a component manager, a shared blackboard, a function container, behavior interaction, behavior output, behavior input, a behavior meta-model, and behavior data, a total of 12 components. The formal description is: SMFBM={LFSM, FFSM, BehCon, EntCon, FunCon, ComMgr, ShrBB, BehItr, BehIpt, BehOpt, BehuMM, BehDat} Among them, SMFBM represents the framework structure of the microscopic behavior simulation model based on the meta-model.

[0037] LFSM represents the Logic Control State Machine, which is used to load the behavior logic of the microscopic behavior model (one of the microscopic behavior model data), and issue instructions to the Function State Machine according to the behavior logic to control the operation of one or more Function State Machines; FFSM represents the Function State Machine, which loads and runs the general function class meta-model elements or special function models according to the instructions issued by the Logic State Machine; BehCon represents the Behavior Container, which is used to load two components, the Logic Control State Machine and the Behavior Interaction. It supports reading and writing the input and output of behaviors from and to the entity components through the interaction component, and realizes the control of the Function State Machine in the Function Container through the interaction component; EntCon represents the Entity Container, which is used to load four components, the Shared Blackboard, the Component Manager, the Behavior Input, and the Behavior Output. Through the Component Manager, it realizes the assembly of simulation entities and the loading of behaviors. Through the Behavior Input and the Behavior Output, it encapsulates the input and output interfaces of the engine to realize the standardized input and output of the simulation model; FunCon represents the Function Container, which is used to load the Function State Machine; ComMgr represents the Component Manager, which is used to register, unregister, and read the entity and behavior components loaded inside the simulation model; ShrBB represents the Shared Blackboard, which supports the storage, reading, and writing functions of the model dynamic state data and the model static parameter data, and supports the mutex for writing; BehItr represents the Behavior Interaction Component, which supports data interaction between entities and between different components inside entities; BehIpt represents the Behavior Input, which is used to receive three types of input data, namely the control instructions, instantiation, and interaction of the simulation model. It supports loading the corresponding behavior data according to the control instructions, generating microscopic simulation behaviors using the Behavior Container, creating a simulation model instance according to the instantiation data, and parsing the semantic of the interaction data between models and between components inside the model; BehOpt represents the Behavior Output, which is used to realize the output of the model state, events, interactions, and creation and cancellation of entities. The state output refers to recording the running process of the model to support the model state for data analysis. The event refers to the key model state changes. The interaction refers to the interaction semantics parsed according to the behavior input, and using the interaction component to realize the detection, communication, etc. of the interaction between models and between components inside the model. The creation and cancellation of entities refer to the output of the creation of new models and the cancellation of existing models during the execution of behaviors, such as taking off an airplane at the airport and landing after the airplane reaches the destination; BehMM represents the Microscopic Behavior Meta-Model, which includes the function class meta-model elements and the control class meta-model elements. For details, please refer to the above text; BehDat represents behavioral data, including three types of data: model parameters, microscopic behavior models, and dynamic libraries of dedicated function models.

[0038] The microscopic behavior models and microscopic behavior meta-models to be constructed will build a simulation model in the form of components. The meta-model technology can be used to model the entire behavior space in a low-code form, improving the efficiency of behavior modeling. Additionally, the general function class meta-model elements in the microscopic behavior meta-model can be directly used to reuse general functions, eliminating the need to re-develop general functions for each simulation model. Furthermore, by designing the function class meta-model elements and control class meta-model elements in the microscopic behavior meta-model, the functions and controls of behaviors are decoupled, technically supporting the modeling of behaviors at any granularity and the combination of behaviors at different granularities, solving the problem of difficult reuse of behaviors at different levels and greatly improving the development efficiency and reusability of simulation models.

[0039] Based on the same inventive concept, such as Figure 3 This application also proposes a meta-model-based device for constructing a behavior-centered simulation model. The device includes: A meta-model construction module 110 for constructing a microscopic behavior meta-model; the microscopic behavior refers to the behavior associated with the microscopic minimum distinguishable entities for constructing a complex system; the microscopic behavior meta-model includes control class meta-model elements and function class meta-model elements; A behavior model construction module 120 for constructing a microscopic behavior model including three behavior levels based on the function class meta-model elements and control class meta-model elements in the microscopic behavior meta-model; A simulation model construction module 130 for constructing a simulation model centered on the microscopic behavior model.

[0040] For the specific limitations of the device, reference can be made to the limitations on the method in the above text, which will not be elaborated here. Each module in the above device can be implemented in whole or in part through software, hardware, and their combinations. The above modules can be embedded in the processor of a computer device in hardware form or be independent of it, or be stored in the memory of a computer device in software form for the processor to call and execute the operations corresponding to the above modules.

[0041] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 4As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes the method for constructing a Chinese event relationship extraction model or the Chinese event relationship extraction method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0042] Those skilled in the art can understand that Figure 4 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0043] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it realizes the steps of the method for constructing a behavior center simulation model based on a meta-model described in any of the above embodiments.

[0044] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, it realizes the steps of the method for constructing a behavior center simulation model based on a meta-model described in any of the above embodiments.

[0045] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

Claims

1. A method for constructing a behavior-centered simulation model based on a meta-model, characterized in that The method includes: Constructing a micro-behavior meta-model; the micro-behavior refers to the behavior of constructing the association of the smallest identifiable entities at the micro level of a complex system; the micro-behavior meta-model includes control-class meta-model elements and function-class meta-model elements; Based on the function-class meta-model elements and control-class meta-model elements in the micro-behavior meta-model, constructing a micro-behavior model including three behavior levels; Constructing a simulation model centered on the micro-behavior model.

2. The method according to claim 1, wherein The control-class meta-model elements include start, end, sequence, parallel, selection, and convergence, six control-class meta-model elements.

3. The method according to claim 2, wherein The function-class meta-model elements include two types of function-class meta-model elements: general function-class meta-model elements and special function-class meta-model elements.

4. The method according to claim 3, wherein The general function-class meta-model elements specify the loading, input, output, and call interfaces of the general function, and are formally described as: ； Among them, represents the set of function model interfaces specified by the general function class meta-model elements, represents the loading interface, which, when used, realizes the loading of the component dynamic library into memory; represents the input interface. Each time a function component is used, this interface needs to be called first to assign values to the function calculation parameters; represents the call interface. After calling the input interface, this interface is called to specify the specific function in the component dynamic library to be called for function calculation to generate the required output; represents the output interface. After each use of the function component, the output result of the function calculation is obtained by calling this interface.

5. The method according to claim 4, wherein The special function-class meta-model elements include six elements: loading function, assembly behavior, entity generation, entity cancellation, model output, and model interaction; Formally described as: ； Among them, represents the loading function, that is, loading a dedicated function model component from the model library; represents the assembly behavior, that is, loading a behavior from the model library and combining it with the behavior being edited; represents the generation of an entity, that is, creating an entity of a specified type and assigning initial parameters to it; represents the destruction of an entity, that is, deregistering a specified entity from the simulation engine to let it exit the simulation; represents the model output, that is, outputting the latest state of this entity and the events generated by key state changes; represents the model interaction, that is, the information interaction that this entity needs to perform with other entities or other components within the entity.

6. The method according to claim 5, wherein Based on the function-class meta-model elements and control-class meta-model elements in the micro-behavior meta-model, constructing a micro-behavior model including three behavior levels, including: Dividing the simulation behavior into function-level behavior, action-level behavior, and task-level behavior; among them, the function-level behavior refers to the general function or special function, the action-level behavior refers to the smallest identifiable behavior ability provided by a specific entity, and the task-level behavior refers to the behavior that can complete an independent business ability; Developing a special function model based on the special function-class meta-model elements, and the special function corresponding to the special function model exists in the form of a loadable dynamic library; Based on the control-class meta-model elements, special function model, and general function-class meta-model elements, constructing two types of behavior at the action level and task level in the form of a tree structure.

7. The method according to claim 6, characterized in that, The method further includes: Running the micro-behavior model based on a hierarchical finite state machine.

8. The method according to claim 7, wherein The hierarchical finite state machine includes an upper-layer behavior logic control state machine and a lower-layer function state machine; Running the micro-behavior model based on the hierarchical finite state machine includes: The upper-layer behavior logic control state machine is used to parse the behavior logic of the micro-behavior model and issue function execution instructions to the lower-layer state machine according to the behavior logic sequence; The lower-layer function state machine is used to load the general function-class meta-model elements or special function models according to the control instructions issued by the upper-layer behavior logic control state machine and execute the specified behavior.

9. The method according to claim 8, wherein The simulation model centered on the micro-behavior model includes the following components: Logic control state machine, functional state machine, behavior container, entity container, function container, component manager, shared blackboard, behavior interaction, behavior output, behavior input, the micro-behavior meta-model and behavior data; wherein, the behavior container is at least used to load the logic control state machine; the function container is at least used to load the functional state machine; the behavior data includes a micro-behavior model and a dedicated function model dynamic library.

10. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

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