@inproceedings{a0fe7a3c41fc4c268a5c18f6eb59e604,
title = "Multi-View Deep Attention Network for Reinforcement Learning",
abstract = "The representation approximated by a single deep network is usually limited for reinforcement learning agents. We propose a novel multi-view deep attention network (MvDAN), which introduces multi-view representation learning into the reinforcement learning task for the first time. The proposed model approximates a set of strategies from multiple representations and combines these strategies based on attention mechanisms to provide a comprehensive strategy for a singleagent. Experimental results on eight Atari video games show that the MvDAN has effective competitive performance than single-view reinforcement learning methods.",
author = "Yueyue Hu and Shiliang Sun and Xin Xu and Jing Zhao",
note = "Publisher Copyright: {\textcopyright} 2020 The Twenty-Fifth AAAI/SIGAI Doctoral Consortium (AAAI-20). All Rights Reserved.; 34th AAAI Conference on Artificial Intelligence, AAAI 2020 ; Conference date: 07-02-2020 Through 12-02-2020",
year = "2020",
language = "英语",
series = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
publisher = "AAAI press",
pages = "13811--13812",
booktitle = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
}