CN114741853A - Simulation operation platform and method based on universal blackboard system - Google Patents
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Abstract
The application relates to a simulation operation platform and a simulation operation method based on a universal blackboard system. The simulation operation platform comprises a basic layer, a data layer and a scheduling algorithm layer, wherein: the base layer comprises a plurality of heterogeneous simulation environments supporting different communication modes; the data layer is used for correlating the data of the intelligent combat simulation entity according to the universal blackboard system and synchronizing the data into the corresponding heterogeneous simulation environment; and the scheduling algorithm layer is used for responding to the simulation instruction, scheduling and executing the intelligent algorithm on each algorithm node in the scheduling algorithm layer according to the time sequence, editing the attribute data of the intelligent combat simulation entity in the data layer and realizing the simulation in the heterogeneous simulation environment. By adopting the simulation operation platform, the combat simulation flexibility and the model flexibility can be improved.
Description
Technical Field
The application relates to the technical field of simulation, in particular to a simulation operation platform and a simulation operation method based on a universal blackboard system.
Background
In recent years, with continuous innovation of artificial intelligence technology, a new generation of multipurpose and whole-field simulation deduction platform is introduced by introducing artificial intelligence technologies such as knowledge maps, multi-agent reinforcement learning and incomplete information games, so that multiplication and energization are realized, and the practical requirements of future intelligent battles on battle simulation are met.
The combat simulation needs to model equipment and force systems of different arms, needs to integrate different types of models, and the models often have different attributes such as resolution, granularity and the like and have complex relationships such as inheritance, combination, interaction, command control and the like. The combat mode in the prior art is based on equipment, and an object-oriented mode is adopted for modeling, so that the problems of low flexibility and poor model flexibility exist.
Disclosure of Invention
In view of the above, there is a need to provide a simulation operation platform, a method, a computer device, a computer readable storage medium and a computer program product based on a universal blackboard system, which can improve the flexibility of combat simulation and the flexibility of models.
In a first aspect, the application provides a simulation operation platform based on a universal blackboard system. The simulation operation platform comprises a basic layer, a data layer and a scheduling algorithm layer, wherein:
the base layer comprises a plurality of heterogeneous simulation environments supporting different communication modes;
the data layer is used for associating the data of the intelligent combat simulation entity according to the universal blackboard system and synchronizing the data into the corresponding heterogeneous simulation environment;
and the scheduling algorithm layer is used for responding to a simulation instruction, scheduling and executing the intelligent algorithm on each algorithm node in the scheduling algorithm layer according to the time sequence, editing the attribute data of the intelligent combat simulation entity in the data layer and realizing the simulation in the heterogeneous simulation environment.
In one embodiment, the scheduling algorithm layer is further configured to update the intelligent algorithm of the target algorithm node on the algorithm tree according to the combat simulation requirement.
In one embodiment, the heterogeneous simulation environment includes at least any one of a reflective memory network system, middleware, a distributed system, and a high performance parallel system.
In one embodiment, the data interaction between the intelligent algorithms is realized through the data layer; each intelligent algorithm is used for realizing a specific task of the combat simulation entity.
In one embodiment, the data of the combat simulation entity is stored in a federated data store of the data layer; the combined data storage library comprises a main entity table, an entity table, a descriptor table and a message table; the main entity table describes all intelligent combat units in the data layer; the entity table is used for describing specific type information of the intelligent combat unit in the application domain; the descriptor table describes data structures of different dimensions of the intelligent combat unit; the message table contains messages of a particular type.
In a second aspect, the application also provides a simulation operation method based on the universal blackboard system. The device comprises:
determining an intelligent combat simulation entity and acquiring application data of the intelligent combat simulation entity;
correlating the application data according to a general blackboard system, and synchronizing the application data to a corresponding heterogeneous simulation environment;
and editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series intelligent algorithm tree to realize simulation in the heterogeneous simulation environment.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:
determining an intelligent combat simulation entity and acquiring application data of the intelligent combat simulation entity;
correlating the application data according to a general blackboard system, and synchronizing the application data to a corresponding heterogeneous simulation environment;
and editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series intelligent algorithm tree to realize simulation in the heterogeneous simulation environment.
In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:
determining an intelligent combat simulation entity and acquiring application data of the intelligent combat simulation entity;
correlating the application data according to a general blackboard system, and synchronizing the application data to a corresponding heterogeneous simulation environment;
and editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series intelligent algorithm tree to realize simulation in the heterogeneous simulation environment.
In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
determining an intelligent combat simulation entity and acquiring application data of the intelligent combat simulation entity;
correlating the application data according to a general blackboard system, and synchronizing the application data to a corresponding heterogeneous simulation environment;
and editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series intelligent algorithm tree to realize simulation in the heterogeneous simulation environment.
The simulation running platform, the method, the computer equipment, the storage medium and the computer program product based on the universal blackboard system have the advantages that the base layer of the simulation running platform comprises heterogeneous simulation environments supporting different communication modes; the data layer associates the data of the intelligent combat simulation entity according to the universal blackboard system and synchronizes the data to the heterogeneous simulation environment of the basic layer; and responding to the simulation instruction, scheduling and executing the intelligent algorithm on each algorithm node in the scheduling algorithm layer according to the time sequence, and editing the attribute data of the intelligent combat simulation entity in the data layer to realize simulation in a heterogeneous simulation environment. The simulation operation platform realizes the separation of an intelligent algorithm and entity data and the editing and synchronization of the entity data by dispersing the functions of equipment, and improves the flexibility of combat simulation and the flexibility of models.
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FIG. 1 is a block diagram of a framework for a universal blackboard system based simulation runtime platform in one embodiment;
FIG. 2 is a schematic diagram of a framework of a simulation operation platform based on a universal blackboard system in another embodiment;
FIG. 3 is a schematic flow chart of a simulation run method based on a universal blackboard system in one embodiment;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a schematic frame diagram of a simulation running platform based on a universal blackboard system is provided, the simulation running platform comprises a base layer, a data layer and a scheduling algorithm layer, and the scheduling of an intelligent algorithm in the scheduling algorithm layer is a circular scheduling; wherein:
the base layer comprises a plurality of heterogeneous simulation environments supporting different communication modes.
The simulation operation platform based on the universal blackboard system adopts a multi-intelligent system (MAS). Multi-intelligence systems mimic the approach of human problem solving, i.e., breaking a problem into smaller sub-problems, each of which can be more easily solved using an algorithm, with the solution (algorithm) of one sub-problem as the input to the solution of another problem. In the application scene of intelligent combat, an intelligent combat equipment can be regarded as an intelligent combat entity, the function of the equipment is decomposed into more combat nodes by the intelligent combat, and the combat nodes are intelligent combat units, namely the intelligent combat is composed of fragment-shaped, numerous and group intelligent combat units with single combat function. That is, an intelligent combat unit may be implemented as a collection of intelligent algorithms and attributes.
The application scene of intelligent combat comprises simulation of countermeasure, scientific research demonstration of weaponry, combat experiments, and innovative research of a combat law; the simulated confrontation refers to the support of establishing a planned scene to carry out battlefield simulated confrontation by editing a map environment, the support of three modes of man-machine, man-man and automatic deduction, the simulation and presentation of various conditions occurring in real battle and the playback analysis of action process, and the improvement of tactical thinking, battle command and on-the-air handling capacity of commanders. The weapon equipment scientific research demonstration is to support four types of typical applications of weapon equipment preliminary research, model demonstration, system demonstration and combat use research, analyze the capability requirement satisfaction degree of the equipment in the confrontation environment, demonstrate the main combat technical indexes of the equipment, evaluate the feasibility and the rationality of the equipment construction scheme and evaluate the contribution degree of the equipment performance to the system combat effectiveness. The combat experiment refers to supporting modeling simulation on battlefield environment, battlefield entity, battlefield behavior, combat action and the like under tactical countermeasure, constructing a simulation model capable of carrying out large sample simulation calculation and data analysis, providing support for the whole process from experiment scheme drawing, experiment factor setting, experiment planning operation to experiment analysis and evaluation, and meeting the requirements of combat commanders and combat researchers on carrying out simulation experiments such as combat theoretical research, combat scheme analysis and evaluation and the like. The war innovative research means that the fighting concept and the war are shown in the experimental environment, the fighting process and the result are observed through the simulation of the fighting process, the crisis, the challenge and the potential opponent facing the battlefield are analyzed, and the purposes of checking the fighting war, verifying the fighting concept and designing the future war are achieved.
The base layer comprises a plurality of heterogeneous simulation environments supporting different communication modes; the heterogeneous simulation environment at least comprises any one of a reflective memory network system, a middleware, a distributed system and a high-performance parallel system. That is to say, the simulation running platform in this embodiment can support any one environment of a reflective memory network system, a middleware, a distributed system and a high-performance parallel system, and implement intelligent combat simulation.
And the data layer is used for correlating the data of the intelligent combat simulation entity according to the universal blackboard system and synchronizing the data into the corresponding heterogeneous simulation environment.
The combat simulation needs modeling of equipment and force systems of different arms, needs integration of models of different types, and the models often have attributes such as different resolutions and granularities and have complex relationships such as inheritance, combination, interaction, command and control. The intelligent combat simulation entity is predetermined. The data layer can be, but is not limited to, a universal blackboard system, and the data layer is built on the data layer. And a combined data storage library is established in the universal blackboard system, and the combined data storage library stores the application data of the intelligent combat simulation entity and realizes the association of the data of the intelligent combat simulation entity. The intelligent combat simulation entity comprises intelligent combat equipment in a combat scene and/or components and the like forming the intelligent combat equipment, for example, the intelligent combat equipment A can be regarded as an intelligent combat entity. The intelligent combat equipment B comprises a component 1, a component 2 and a component 3, wherein the component 1, the component 2 and the component 3 can be respectively regarded as an intelligent combat entity.
The combined data repository comprises a main entity table, an entity table, a descriptor table and a message table; the main entity table, the descriptor table and the message table are determined according to the intelligent combat simulation entity. The main entity table describes all intelligent combat units in the data layer; the entity table is used for describing specific type information of the intelligent combat units in the application domain; the descriptor table describes data structures of different dimensions of the intelligent combat unit; the message table contains messages of a particular type and is treated as a circular queue. When data in a message table is full, deleting the data with the earliest writing time according to the data writing time in the message table. The intelligent operation unit decomposes and determines the intelligent operation equipment according to the operation function according to the intelligent operation. The data layer synchronizes the data of the combat simulation entity to the corresponding heterogeneous simulation environment, and calls a corresponding function through an API (application program interface) distribution data interaction interface according to a preset data distribution strategy to realize the synchronous distribution of the data.
And the intelligent algorithm layer is used for responding to the simulation instruction, scheduling and executing the intelligent algorithms on each algorithm node in the scheduling algorithm layer according to the time sequence, editing the attribute data of the intelligent combat simulation entity in the data layer and realizing the simulation in the heterogeneous simulation environment.
Specifically, in the intelligent combat simulation, a scheduling algorithm layer responds to a simulation instruction, triggers a logic process (such as a logic process 1, a logic process n, a logic process m and the like) according to a time sequence, schedules and executes an intelligent algorithm corresponding to the logic process, and accesses attribute data of an intelligent combat simulation entity in a data layer based on a simulation running platform of a universal blackboard system. When detecting that the attribute data of the intelligent combat simulation entity in the data layer is updated, modifying the corresponding attribute data, and synchronizing the modified attribute data to a heterogeneous environment associated with the attribute data. And scheduling in sequence based on the time sequence to realize simulation in a heterogeneous simulation environment. For example, based on the simulation running platform based on the universal blackboard system in the application, the simulation based on the reflective memory network, the distributed simulation based on the distributed environment, the parallel simulation based on the parallel environment and the simulation based on the middleware can be realized.
For example, in an intelligent combat application, two different communication methods (i.e., communication method 1 and communication method 2) are determined, and a simulation model for implementing communication method 1 is different from a simulation model for implementing communication method 2. In a simulation operation platform based on a universal blackboard system, in order to realize a simulation model and simulation operation of a communication mode 1, an intelligent algorithm for realizing the communication mode 1 in an intelligent algorithm layer is scheduled and executed according to a time sequence by responding to a simulation instruction, attribute data of a corresponding intelligent combat simulation entity in a data layer is edited, and simulation on a corresponding heterogeneous simulation environment in a basic layer is realized.
In a simulation operation platform based on a universal blackboard system, in order to realize a simulation model and simulation operation of a communication mode 2, an intelligent algorithm for realizing the communication mode 2 in an intelligent algorithm layer is scheduled and executed according to a time sequence by responding to a simulation instruction, attribute data of a corresponding intelligent combat simulation entity in a data layer is edited, and simulation on a corresponding heterogeneous simulation environment in a basic layer is realized.
Each intelligent algorithm in the scheduling algorithm layer can realize and can only realize the specific functions of the intelligent combat unit; according to the actual simulation requirements, the data layer carries out scheduling execution on the intelligent algorithm in the algorithm layer, the fighting behaviors with specific functions of the intelligent fighting units are realized, and then all the fighting behaviors are completed. All intelligent algorithms in the algorithm layer are organized in a tree structure, and each node on the tree is an intelligent algorithm; the hierarchy exists between nodes, and the hierarchy between the nodes is predefined. For example, the node 1 is a high-level node, the node 2 is a low-level node, the intelligent algorithm on the node 1 is an abstraction of the intelligent algorithm on the node 2, and the intelligent algorithm on the node 2 can further derive, expand and refine the intelligent algorithm on the node 1.
The simulation running platform based on the universal blackboard system comprises heterogeneous simulation environments supporting different communication modes in a basic layer; the data layer correlates the data of the intelligent combat simulation entity according to the universal blackboard system, and synchronizes the data to the heterogeneous simulation environment of the base layer to realize the sharing of the data; the scheduling algorithm layer responds to the simulation instruction, performs scheduling and executing the intelligent algorithm on each algorithm node in the scheduling algorithm layer according to the time sequence, accesses and modifies the attribute data of the intelligent combat simulation entity in the data layer, and realizes simulation in a heterogeneous simulation environment. The simulation operation platform realizes the separation of the intelligent algorithm and the entity data by dispersing the functions of the simulation platform, and accesses and updates the intelligent simulation entity data in real time by scheduling the intelligent algorithm, thereby improving the combat simulation flexibility and the model flexibility.
In another embodiment, as shown in FIG. 2, a schematic diagram of a framework of a simulation runtime platform based on a universal blackboard system is provided, the simulation runtime platform comprises a base layer, a data layer and a scheduling algorithm layer. The base layer comprises a reflective memory network system, a middleware, a distributed system and a high-performance parallel system.
The reflective memory network is a ring/star-based high-speed copy shared memory network. A real-time network constructed based on a reflective memory (RFM) is a strong real-time high-bandwidth local area network and can provide efficient data transmission among interconnected computer systems. The reflective memory network can virtualize a section of globally shared network memory in all interconnected computer nodes, so as to achieve the purpose of memory-to-memory communication in a distributed system. Distributed environments are those where computers at different physical locations are connected by a network (or the Internet), as well as portable computers that utilize wireless connections. Parallel environments consist of shared-memory multiprocessors, multiple computer systems, or Single Instruction Multiple Data (SIMD) machines, with the goal of providing a better computing environment for parallel execution of programs. The middleware is positioned above an operating system, a network and a database and below application software and aims to manage computing resources and network communication, and the middleware is used for providing an operation and development environment for the application software on the upper layer of the middleware and helping a user to develop and integrate complex application software flexibly and efficiently.
The data layer is a universal blackboard system, a combined data storage library is established in the data layer, and application data of the whole simulation system in the operation period are stored in the combined data storage library; and the entity data of the combat simulation entity of the data layer can be synchronized to the corresponding heterogeneous environment of the base layer based on a universal blackboard mechanism. The scheduling algorithm layer comprises intelligent algorithms for realizing intelligent combat behaviors, and each intelligent algorithm is used for realizing a specific task of a combat simulation entity. The intelligent algorithm comprises a learning algorithm, a detection algorithm, a judgment algorithm, a decision algorithm, a striking algorithm, a damage algorithm and the like.
The interaction between the intelligent algorithms is realized through a universal blackboard system.
The interactive mechanism of the universal blackboard system comprises an annular data interactive mechanism, a data routing parallel retrieval mechanism, a multi-strategy data synchronous distribution mechanism, a differentiated data updating mechanism, an entity state updating logic separation mechanism and the like; the ring data interaction mechanism realizes ring data interaction between intelligent algorithms through queues. The data route parallel retrieval mechanism realizes the parallel retrieval of the data routes between the intelligent algorithms by setting a publish/subscribe mechanism between the intelligent algorithms; the parallel search can be, but is not limited to, a multi-node, multi-thread and multi-process three-level parallel search.
The multi-strategy data synchronous distribution mechanism is used for synchronously distributing data among intelligent algorithms through an API (application programming interface) distribution data interaction interface. The differentiated data updating mechanism is that when the intelligent algorithm receives the entity state of the simulation entity, the entity cache region is updated by comparing the entity state difference information stored in the intelligent algorithm with the entity state difference information. Further, in one embodiment, the scheduling algorithm layer is further configured to update the intelligent algorithm of the target algorithm node on the algorithm tree according to the combat simulation requirement. It can be understood that in the simulation operation platform based on the universal blackboard system, the intelligent algorithm and the data are separated from each other, the entity data in the data layer can be accessed and modified by scheduling the intelligent algorithm, and the data in the data layer can be synchronized to the corresponding heterogeneous simulation environment. Furthermore, data synchronization among the intelligent algorithm nodes can be realized through a universal blackboard management system in a data layer, and the accuracy of entity data is ensured.
In the simulation process based on the simulation operation platform, the intelligent combat simulation entity A executes an intelligent algorithm through a scheduling algorithm layer based on time sequence scheduling, and accesses and modifies entity data of the intelligent combat simulation entity A in a data layer.
The simulation running platform based on the universal blackboard system stores application data of the whole simulation system in a combined data storage library of a data layer during running; intelligent algorithms in the scheduling algorithm layer are sequentially scheduled and executed based on the time sequence in the simulation process, and the combat simulation entity data can be accessed and modified. And synchronizing the combat simulation entity data to the heterogeneous environment corresponding to the base layer through a universal blackboard system of the data layer. The simulation operation platform improves the combat simulation flexibility and the model flexibility by dispersing the equipment functions, realizing the separation of an intelligent algorithm and entity data and editing and synchronizing the entity data. The simulation operation platform based on the universal blackboard system divides functions of intelligent combat equipment, adopts a model with finer granularity for modeling, has the characteristics of self-adaptive construction, dynamic recombination and the like, and improves the flexibility of modeling.
Based on the same inventive concept, the embodiment of the application also provides a simulation operation method based on the universal blackboard system for realizing the simulation operation platform based on the universal blackboard system. The implementation scheme for solving the problem provided by the method is similar to the implementation scheme recorded in the simulation running platform, so that specific limitations in one or more embodiments of the simulation running method based on the universal blackboard system provided below can be referred to the limitations of the simulation running platform based on the universal blackboard system, and are not described herein again.
In an embodiment, as shown in fig. 3, a simulation running method based on a universal blackboard system is provided, and this embodiment is illustrated by applying the method to a terminal, it is to be understood that the method may also be applied to a server, and may also be applied to a system including a terminal and a server, and is implemented by interaction between the terminal and the server. In this embodiment, the method includes the steps of:
The intelligent combat simulation entity comprises intelligent combat equipment in a combat scene and/or all components forming the intelligent combat equipment and the like. The application data comprises attribute data of the intelligent combat simulation entity.
And 304, correlating the application data according to the universal blackboard system, and synchronizing the application data to the corresponding heterogeneous simulation environment.
The universal blackboard system mechanism comprises an annular data interaction mechanism, a data routing parallel retrieval mechanism, a multi-strategy data synchronous distribution mechanism, a differentiated data updating mechanism, an entity state updating logic separation mechanism and the like. The heterogeneous simulation environment at least comprises any one of a reflective memory network system, a middleware, a distributed system and a high-performance parallel system.
Specifically, the application data of each intelligent combat simulation entity can be associated according to the universal blackboard system, and data sharing is realized; i.e. the application data is synchronized to the corresponding heterogeneous simulation environment.
And step 306, editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series intelligent algorithm tree, and realizing simulation in a heterogeneous simulation environment.
Specifically, when algorithm scheduling is carried out, an algorithm root node is determined from an algorithm tree; and sequentially scheduling the intelligent algorithms on each node of the intelligent algorithm tree based on the time sequence and the algorithm root node, and accessing and modifying attribute data in the application data to realize simulation in a heterogeneous simulation environment. The root node is an abstract algorithm, mainly provides an abstract interface and is responsible for providing an algorithm execution mode for the intelligent combat simulation platform. The intelligent combat simulation platform can realize the calling of all intelligent algorithms by calling the algorithm interface and utilizing the object-oriented heavy load characteristic. The nodes in the algorithm tree have hierarchical levels which are preset, the algorithm of the high-level nodes in the algorithm tree is abstract of the algorithm of the low-level nodes, and the algorithm of the low-level nodes is further derivation, expansion and refinement of the algorithm of the high-level nodes.
Optionally, in an embodiment, the simulation running method based on the universal blackboard system further includes: responding to an algorithm updating instruction; the algorithm updating instruction carries the node identification; and updating the intelligent algorithm of the target algorithm node on the algorithm tree according to the node identification.
Specifically, according to the combat simulation requirements, when the intelligent algorithm needs to be updated, an algorithm updating instruction is triggered and generated; responding to the algorithm updating instruction, and acquiring algorithm updating data; and updating the intelligent algorithm of the target algorithm node matched with the node identifier on the algorithm tree according to the algorithm updating data.
Optionally, in one embodiment, the data of the combat simulation entity is stored in a federated data store of the data layer; the combined data repository comprises a main entity table, an entity table, a descriptor table and a message table; the main entity table describes all intelligent combat units in the data layer; the entity table is used for describing specific type information of the intelligent combat unit in the application domain; the descriptor table describes data structures of different dimensions of the intelligent combat unit; the message table contains messages of a particular type. Wherein, the intelligent combat unit is determined according to the combat function. For example, in one simulation application scenario, a drone is included for implementing different functions; wherein each unmanned aerial vehicle realizing different functions is an intelligent combat unit.
In the simulation operation method based on the universal blackboard system, the data of the intelligent combat simulation entity is associated according to the universal blackboard system, and the data is synchronized to the heterogeneous simulation environment; and responding to the simulation instruction, scheduling and executing the intelligent algorithm on each algorithm node according to the time sequence, editing the attribute data of the intelligent combat simulation entity, and realizing the simulation in the heterogeneous simulation environment. The simulation operation platform realizes the separation of an intelligent algorithm and entity data by dispersing the functions of equipment, and the editing and synchronization of the entity data, thereby improving the flexibility of combat simulation and the flexibility of models.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a simulated operation method based on a universal blackboard system. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the configuration shown in fig. 4 is a block diagram of only a portion of the configuration associated with the present application, and is not intended to limit the computing device to which the present application may be applied, and that a particular computing device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. The utility model provides a simulation operation platform based on general blackboard system which characterized in that, simulation operation platform includes basic layer, data layer and scheduling algorithm layer, wherein:
the base layer comprises a plurality of heterogeneous simulation environments supporting different communication modes;
the data layer is used for associating the data of the intelligent combat simulation entity according to the universal blackboard system and synchronizing the data into the corresponding heterogeneous simulation environment;
and the scheduling algorithm layer is used for responding to a simulation instruction, scheduling and executing the intelligent algorithm on each algorithm node in the scheduling algorithm layer according to the time sequence, editing the attribute data of the intelligent combat simulation entity in the data layer and realizing the simulation in the heterogeneous simulation environment.
2. The simulation running platform according to claim 1, wherein the scheduling algorithm layer is further configured to update the intelligent algorithm of the target algorithm node on the algorithm tree according to the combat simulation requirement.
3. The emulation runtime platform of claim 1, wherein the heterogeneous emulation environment comprises at least any one of a reflective memory network system, middleware, a distributed system, and a high performance parallel system.
4. The simulation runtime platform of claim 1, wherein data interaction between the scheduling algorithms is implemented through the data layer; each intelligent algorithm is used for realizing a specific task of the combat simulation entity.
5. The simulation runtime platform of claim 1, wherein the data of the combat simulation entity is stored in a federated data store of the data tier; the combined data repository comprises a main entity table, an entity table, a descriptor table and a message table; the main entity table describes all intelligent combat units in the data layer; the entity table is used for describing specific type information of the intelligent combat unit in the application domain; the descriptor table describes data structures of different dimensions of the intelligent combat unit; the message table contains messages of a particular type.
6. A simulation operation method based on a universal blackboard system is characterized by comprising the following steps:
determining an intelligent combat simulation entity and acquiring application data of the intelligent combat simulation entity;
correlating the application data according to a general blackboard system, and synchronizing the application data to a corresponding heterogeneous simulation environment;
and editing attribute data in the application data based on the intelligent algorithm on each algorithm node on the time series scheduling algorithm tree to realize simulation in the heterogeneous simulation environment.
7. The method of claim 6, further comprising:
responding to the updating instruction; the updating instruction carries the node identification;
and updating the intelligent algorithm of the target algorithm node on the algorithm tree according to the node identification.
8. The method of claim 6, wherein the data of the combat simulation entity is stored in a federated data store of the data tier; the combined data storage library comprises a main entity table, an entity table, a descriptor table and a message table; the main entity table describes all intelligent combat units in the data layer; the entity table is used for describing specific type information of the intelligent combat unit in the application domain; the descriptor table describes data structures of different dimensions of the intelligent combat unit; the message table contains messages of a particular type.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 6 to 8 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 6 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115858205A (en) * | 2023-02-27 | 2023-03-28 | 中国人民解放军国防科技大学 | Memory blackboard mechanism-based simulation component interaction method, device and equipment |
| CN116069530A (en) * | 2023-04-03 | 2023-05-05 | 中国人民解放军国防科技大学 | Simulation engine data sharing blackboard system based on memory pool |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392279A (en) * | 2014-11-19 | 2015-03-04 | 天津大学 | Operation optimization method for multi-agent-structure micro-grids |
| CN105630578A (en) * | 2015-12-24 | 2016-06-01 | 中国人民解放军海军航空工程学院 | Distributed multi-agent system-based combat simulation engine |
| CN110781584A (en) * | 2019-10-11 | 2020-02-11 | 南京智能仿真技术研究院有限公司 | Intelligent simulation combat system of air force unmanned aerial vehicle |
-
2022
- 2022-03-25 CN CN202210301161.9A patent/CN114741853A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104392279A (en) * | 2014-11-19 | 2015-03-04 | 天津大学 | Operation optimization method for multi-agent-structure micro-grids |
| CN105630578A (en) * | 2015-12-24 | 2016-06-01 | 中国人民解放军海军航空工程学院 | Distributed multi-agent system-based combat simulation engine |
| CN110781584A (en) * | 2019-10-11 | 2020-02-11 | 南京智能仿真技术研究院有限公司 | Intelligent simulation combat system of air force unmanned aerial vehicle |
Non-Patent Citations (2)
| Title |
|---|
| QINGJUN QU ET AL.: "Research on Simulation Platform for Intelligent Warfare", 《2022 2ND ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE (ACCTCS)》, 27 February 2022 (2022-02-27), pages 160 - 163, XP034149798, DOI: 10.1109/ACCTCS53867.2022.00041 * |
| 王幸军;唐晨;: "基于GBB技术海军作战仿真中水下探测和水声对抗设计与实现", 指挥控制与仿真, vol. 42, no. 02, 17 October 2019 (2019-10-17), pages 100 - 104 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115858205A (en) * | 2023-02-27 | 2023-03-28 | 中国人民解放军国防科技大学 | Memory blackboard mechanism-based simulation component interaction method, device and equipment |
| CN115858205B (en) * | 2023-02-27 | 2023-05-02 | 中国人民解放军国防科技大学 | Simulation component interaction method, device and equipment based on memory blackboard mechanism |
| CN116069530A (en) * | 2023-04-03 | 2023-05-05 | 中国人民解放军国防科技大学 | Simulation engine data sharing blackboard system based on memory pool |
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