Replanning in Domains with Partial Information and Sensing Actions
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2021-2025.
Abstract
Replanning via determinization is a recent, popular approach for onlineplanning in MDPs. In this paper we adapt this idea to classical,non-stochastic domains with partial information and sensing actions. At eachstep we generate a candidate plan which solves a classical planning probleminduced by the original problem. We execute this plan as long as it is safeto do so. When this is no longer the case, we replan.The classical planning problem we generate is based on the T0 translation, in which the classical state captures the knowledge state of theagent. We overcome the non-determinism in sensing actions, and the large domain size introduced by T0 by using state sampling. Our planner also employs a novel, lazy, regression-based method for querying the belief state.
@inproceedings{ijcai2011p337,
title = {Replanning in Domains with Partial Information and Sensing Actions},
author = {Shani, Guy and Brafman, Ronen I.},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2021--2025},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-337},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-337},
}
TY - CPAPER TI - Replanning in Domains with Partial Information and Sensing Actions AU - Shani, Guy AU - Brafman, Ronen I. T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2021 EP - 2025 DO - 10.5591/978-1-57735-516-8/IJCAI11-337 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-337 ER -Copied
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