Learning Spatial Search using Submodular Inverse Reinforcement Learning

Ji Jie Wu, Kuo Shih Tseng

研究成果: 書貢獻/報告類型會議論文篇章同行評審

1 引文 斯高帕斯(Scopus)

摘要

Finding an optimal search path is a NP-hard problem. Since search is one of human central activities, learning spatial search behavior from human operators is a way to solve search problems. Utilizing the submodularity of search problems, this research proposes a submodular inverse reinforcement learning (SIRL) algorithm to learn humans' search behavior. The experiments demonstrate that the performance of the learned search paths outperform that of state of the art approaches (e.g., MaxEnt IRL and DIRL).

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主出版物標題2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020
編輯Lino Marques, Majid Khonji, Jorge Dias
發行者Institute of Electrical and Electronics Engineers Inc.
頁面7-14
頁數8
ISBN(電子)9781665403900
DOIs
出版狀態已出版 - 4 11月 2020
事件2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020 - Abu Dhabi, United Arab Emirates
持續時間: 4 11月 20206 11月 2020

出版系列

名字2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020

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???event.eventtypes.event.conference???2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020
國家/地區United Arab Emirates
城市Abu Dhabi
期間4/11/206/11/20

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