海空跨域协同兵棋AI架构设计及关键技术分析OACSTPCD

The breakthrough and progress of intelligent gaming technology with deep reinforcement learning as the core in the field of games provide a method reference for the research of agents in sea-air wargames.The architecture design of the a-gent is the primary core key problem that needs to be solved,and a good architecture can reduce the complexity and difficulty of training and accelerate the convergence of policies.A stochastic game model of sea-air cross-domain cooperative decision-making has been proposed,and its corresponding equilibrium solution concepts have been analyzed.Based on the analysis of typical agent frameworks,aiming at the decision-making gaming process of sea-air wargames,and then an agent bi-level ar-chitecture based on multi-Agent hierarchical reinforcement learning is proposed,which can effectively solve the problems of collaboration and dimensional disaster.The key technologies are analyzed from four aspects:force coordination,agent net-work design,adversary modeling and training mechanism.Hoping to provide architectural guidance for the subsequent design and implementation of sea-air wargaming agents.