Global critic and local actor for campaign-tactic combat management in the joint operation simulation software

Yabin Wang; Pen Cui; Youjiang Li

doi:10.1117/12.2671217

28 April 2023 Global critic and local actor for campaign-tactic combat management in the joint operation simulation software

Yabin Wang, Pen Cui, Youjiang Li

Author Affiliations +

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261016 (2023) https://doi.org/10.1117/12.2671217
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Users of the simulation software not only need to model the capability of each unit, but also need to create a decision maker for the units in the simulation software, to control ships, aircrafts and ground units to cooperates to achieve one goal. In this paper a new approach is constructed to create the decision maker. We use reinforcement learning based on global critic and local actor. The invention constructs an air isomorphic formation command method based on multiagent PPO algorithm. The evaluation network uses global information, so that the algorithm has the ability to evaluate global information and guide the agent to select actions that are beneficial to the global environment state. The input of the action network is local information, so that the agent can focus on local information.

Citation Download Citation

Yabin Wang, Pen Cui, and Youjiang Li "Global critic and local actor for campaign-tactic combat management in the joint operation simulation software", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261016 (28 April 2023); https://doi.org/10.1117/12.2671217

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