| タイトル | Back to the Future: Consistency-Based Trajectory Tracking |
| 本文（外部サイト） | http://hdl.handle.net/2060/20000115624 |
| 著者（英） | Nayak, P. Pandurand; Norvig, Peter; Kurien, James |
| 著者所属（英） | NASA Ames Research Center |
| 発行日 | 2000-01-01 |
| 言語 | eng |
| 内容記述 | Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the process and the actions required to move the process to a desired configuration. We introduce a representation and algorithms for incrementally generating approximate belief states for a restricted but relevant class of partially observable Markov decision processes with very large state spaces. The algorithm presented incrementally generates, rather than revises, an approximate belief state at any point by abstracting and summarizing segments of the likely trajectories of the process. This enables applications to efficiently maintain a partial belief state when it remains consistent with observations and revisit past assumptions about the process' evolution when the belief state is ruled out. The system presented has been implemented and results on examples from the domain of spacecraft control are presented. |
| NASA分類 | Cybernetics, Artificial Intelligence and Robotics |
| 権利 | No Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/226604 |
