A Three-Dimensional Pursuit-Evasion Game Based on Fuzzy Actor-Critic Learning Algorithm

2025/03/11 by Penglin Hu, Hu, Penglin
Computer Science · Engineering · #Artificial Intelligence in Games #Evacuation and Crowd Dynamics #FOS: Electrical engineering #Guidance and Control Systems #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2503.08013

openalex publication_date 2025/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Most of the existing research on pursuit-evasion game (PEG) is conducted in a two-dimensional (2D) environment. In this paper, we investigate the PEG in a 3D space. We extend the Apollonius circle (AC) to the 3D space and introduce its detailed analytical form. To enhance the capture efficiency, we derive the optimal motion space for both the pursuer and the evader. To address the issue arising from a discrete state space, we design a fuzzy actor-critic learning (FACL) algorithm to obtain the agents' strategies. To improve learning performance, we devise a reward function for the agents, which enables obstacle avoidance functionality. The effectiveness of the proposed algorithm is validated through simulation experiments.

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