@inproceedings{97dfccc6d8064a92b98cc79755babbcf,
title = "Cooperative Game-based Multi-Agent Path Planning with Obstacle Avoidance",
abstract = "This paper investigates multi-agent cooperative path planning with obstacle avoidance based on game theory and multi-agent reinforcement learning algorithm. It aims to extend the traditional single agent Q-learning algorithm to multi-agent systems by using the cooperative game framework. This framework takes into account the selection of joint actions at joint states for multi-agent cooperative path planning with obstacle avoidance. First, a cooperative game model is presented for agents to achieve cooperative path planning with obstacle avoidance in complicated environment. Second, a multi-agent Q-learning algorithm in continuous state space is proposed for solving Nash equilibrium, where the local minimum problem is well resolved. Finally, a numerical example is conducted to verify the effectiveness of the proposed approach.",
keywords = "cooperative game, obstacle avoidance, path planning, Reinforcement learning",
author = "Yaning Guo and Quan Pan and Qi Sun and Chunhui Zhao and Dong Wang and Min Feng",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 28th IEEE International Symposium on Industrial Electronics, ISIE 2019 ; Conference date: 12-06-2019 Through 14-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ISIE.2019.8781205",
language = "英语",
series = "IEEE International Symposium on Industrial Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1385--1390",
booktitle = "Proceedings - 2019 IEEE 28th International Symposium on Industrial Electronics, ISIE 2019",
}