Pursuit Strategy

Pursuit strategy research focuses on developing algorithms and models for effectively tracking and intercepting moving targets, encompassing diverse applications from autonomous vehicles to multi-agent systems. Current research emphasizes cooperative strategies, leveraging techniques like reinforcement learning (including variations such as DPO and curriculum learning), consensus-based approaches, and opponent-aware models to improve efficiency and robustness in complex, dynamic environments. These advancements have significant implications for various fields, including robotics, autonomous systems, and resource allocation, by enabling more effective coordination and control in challenging scenarios.