@inproceedings{8b70d7e64cd8497ca7f11d8f1086d748,
title = "A Deep Reinforcement Learning Method for Lion and Man Problem",
abstract = "David Gale's lion and man problem, which is a fundamental pursuit-evasion game, attracts the interest of many scholars. We propose a deep reinforcement learning method based on Deep Deterministic Policy Gradient (DDPG) to solve this problem. We first improve the exploration strategy by adding guided exploration and dynamic spaces exploration strategies to the greedy algorithm. Then we introduce a learning reset mechanism to help the agents escape the traps in the learning process. With these improvements, our method achieves better performance than the classic DDPG algorithm in the lion and man problem. The simulation result shows that deep reinforcement learning method may be promising to solve this problem.",
keywords = "Deep Reinforcement Learning, Exploration Strategy, Lion and Man Problem",
author = "Jiebang Xing and Xianlin Zeng",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9550113",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "8366--8371",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "United States",
}