每年專案
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).
原文 | ???core.languages.en_GB??? |
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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 2020 → 6 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 |
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國家/地區 | United Arab Emirates |
城市 | Abu Dhabi |
期間 | 4/11/20 → 6/11/20 |
指紋
深入研究「Learning Spatial Search using Submodular Inverse Reinforcement Learning」主題。共同形成了獨特的指紋。專案
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