Autonomous Decision Making for UAV Cooperative Pursuit-Evasion Game with Reinforcement Learning

TL;DR

This paper introduces a deep reinforcement learning model for autonomous decision-making in multi-UAV pursuit-evasion games, enhancing cooperation and efficiency through a novel training algorithm and role allocation strategies.

Contribution

It proposes a multi-environment asynchronous double deep Q-network with priority experience replay to improve training efficiency in high-dimensional UAV pursuit-evasion scenarios.

Findings

Effective autonomous decision-making demonstrated in simulations.

Enhanced cooperation among UAVs in pursuit-evasion tasks.

Improved task completion efficiency and reduced UAV costs.

Abstract

The application of intelligent decision-making in unmanned aerial vehicle (UAV) is increasing, and with the development of UAV 1v1 pursuit-evasion game, multi-UAV cooperative game has emerged as a new challenge. This paper proposes a deep reinforcement learning-based model for decision-making in multi-role UAV cooperative pursuit-evasion game, to address the challenge of enabling UAV to autonomously make decisions in complex game environments. In order to enhance the training efficiency of the reinforcement learning algorithm in UAV pursuit-evasion game environment that has high-dimensional state-action space, this paper proposes multi-environment asynchronous double deep Q-network with priority experience replay algorithm to effectively train the UAV's game policy. Furthermore, aiming to improve cooperation ability and task completion efficiency, as well as minimize the cost of UAVs in the pursuit-evasion game, this paper focuses on the allocation of roles and targets within multi-UAV environment. The cooperative game decision model with varying numbers of UAVs are obtained by assigning diverse tasks and roles to the UAVs in different scenarios. The simulation results demonstrate that the proposed method enables autonomous decision-making of the UAVs in pursuit-evasion game scenarios and exhibits significant capabilities in cooperation.