尹安. 基于墨子平台的水下攻防算法设计研究[J]. 中国舰船研究, 2023, 19(X): 1–6. doi: 10.19693/j.issn.1673-3185.03154
引用本文: 尹安. 基于墨子平台的水下攻防算法设计研究[J]. 中国舰船研究, 2023, 19(X): 1–6. doi: 10.19693/j.issn.1673-3185.03154
YIN A. Design and Research of Underwater Attack-Defense Algorithm Based On MoZi Platform[J]. Chinese Journal of Ship Research, 2023, 19(X): 1–6. doi: 10.19693/j.issn.1673-3185.03154
Citation: YIN A. Design and Research of Underwater Attack-Defense Algorithm Based On MoZi Platform[J]. Chinese Journal of Ship Research, 2023, 19(X): 1–6. doi: 10.19693/j.issn.1673-3185.03154

基于墨子平台的水下攻防算法设计研究

Design and Research of Underwater Attack-Defense Algorithm Based On MoZi Platform

  • 摘要:
      目的  开展基于墨子平台的水下战场多智能体协同攻防算法设计研究,探索水下无人平台作战应用。
      方法  提出基于墨子平台的设计思路。针对算法处理确定性规则下的行动决策,提出基于知识图谱的设计方法,采用Neo4J图数据库构建全局知识库,并设计数据交换接口,为智能算法模块提供确定性规则的辅助决策信息输入;针对算法处理非确定性和不完全信息下的行动决策,在设定场景下论述基于MADDPG的协同占位决策算法设计,提出了状态空间、动作空间、奖励函数以及与知识图谱模块的交互设计思路。
      结果  介基于上述思路,完成了算法框架总体设计。在墨子平台中实现了知识图谱和智能算法的整合,并通过墨子平台提供的可视化手段,进一步验证了确定性规则下的行为约束与处理非确定性态势信息的智能算法进行整合的有效性。
      结论  仿真结果表明本文研究工作可为后续进一步开展多智能体水下攻防协同算法设计提供参考。

     

    Abstract:
      Objectives  This study focuses on the multi-agent cooperative attack-defense algorithm design of underwater battlefields based on the MoZi platform, and explores the combat application of underwater unmanned platforms.
      Methods  A design idea based on the MoZi platform is proposed. For action decision-making under deterministic rules, the design of knowledge graph modules is discussed. The Neo4J database is used to build a global knowledge database, and a data exchange interface is designed to provide the auxiliary decision information input of deterministic rules for the intelligent algorithm module. For action decision-making under uncertain and incomplete information, the design of a cooperative space occupying a decision-making algorithm based on MADDPG is discussed under the set scenario, and the design concept of a state space, action space, reward function and interaction with the knowledge graph module is put forward.
      Results  The overall design of the algorithm framework is completed on the basis of the abovementioned ideas. The integration of the knowledge graph and intelligent algorithm is realized on the MoZi platform, and the effectiveness of the integration of behavior constraints under deterministic rules and the intelligent algorithm for processing uncertain situation information is further verified through the visualization provided by the platform.
      Conclusions  This paper can provide valuable references for the design of multi-agent underwater attack and defense cooperative algorithms.

     

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