Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning
Finding feasible, collision-free paths for multiagent systems can be challenging, particularly in non-communicating scenarios where each agent's intent (e.g. goal) is unobservable to the others. In particular, finding time efficient paths often requires anticipating interaction with neighboring...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers (IEEE)
2018
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| Online Access: | http://hdl.handle.net/1721.1/114720 https://orcid.org/0000-0003-3756-3256 https://orcid.org/0000-0002-1648-8325 https://orcid.org/0000-0001-9377-6745 https://orcid.org/0000-0001-8576-1930 |