Architecture design and key technologies analysis of wargaming AI for sea-air cross-domain coordination
In: Zhihui kongzhi yu fangzhen, Jg. 46 (2024), Heft 2, S. 35-43
Online
academicJournal
Zugriff:
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 agent 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 architecture 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 network design, adversary modeling and training mechanism. Hoping to provide architectural guidance for the subsequent design and implementation of sea-air wargaming agents.
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Architecture design and key technologies analysis of wargaming AI for sea-air cross-domain coordination
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Autor/in / Beteiligte Person: | SU Jiongming, LUO Junren, CHEN Shaofei, XIANG Fengtao |
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Zeitschrift: | Zhihui kongzhi yu fangzhen, Jg. 46 (2024), Heft 2, S. 35-43 |
Veröffentlichung: | Editorial Office of Command Control and Simulation, 2024 |
Medientyp: | academicJournal |
ISSN: | 1673-3819 (print) |
DOI: | 10.3969/j.issn.1673-3819.2024.02.006 |
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