QMARL: A Quantum Multi-Agent Reinforcement Learning Framework for Swarm Robots Navigation

Author:

Chen Weizhao1,Wan Jiawang1,Ye Fangwen1,Wang Ran1,Xu Cheng1

Affiliation:

1. University of Science and Technology,School of Computer and Communication Engineering,Beijing

Funder

National Natural Science Foundation of China

China Scholarship Council

Publisher

IEEE

Reference17 articles.

1. Multi-agent deep reinforcement learning: a survey

2. A survey of learning in multiagent environments: Dealing with non- stationarity[J];Hernandez-Leal,2017

3. Autonomously Reusing Knowledge in Multiagent Reinforcement Learning

4. Learning to communicate with deep multi-agent reinforcement learning[J];Foerster;Advances in neural information processing systems,2016

5. Value-decomposition networks for cooperative multi-agent learning[J];Sunehag,2017

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