Online Planning for Ad Hoc Autonomous Agent Teams
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 439-444.
Abstract
We propose a novel online planning algorithm for ad hoc team settings — challenging situations in which an agent must collaborate with unknown teammates without prior coordination. Our approach is based on constructing and solving a series of stage games, and then using biased adaptive play to choose actions. The utility function in each stage game is estimated via Monte-Carlo tree search using the UCT algorithm. We establish analytically the convergence of the algorithm and show that it performs well in a variety of ad hoc team domains.
@inproceedings{ijcai2011p81,
title = {Online Planning for Ad Hoc Autonomous Agent Teams},
author = {Wu, Feng and Zilberstein, Shlomo and Chen, Xiaoping},
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 = {439--444},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-081},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-081},
}
TY - CPAPER TI - Online Planning for Ad Hoc Autonomous Agent Teams AU - Wu, Feng AU - Zilberstein, Shlomo AU - Chen, Xiaoping 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 - 439 EP - 444 DO - 10.5591/978-1-57735-516-8/IJCAI11-081 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-081 ER -Copied
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