Bimodal Switching for Online Planning in Multiagent Settings
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 360-365.
Abstract
We present a bimodal method for online planning in partially observable multiagent settings as formalized by a finitely-nested interactive partially observable Markov decision process (I-POMDP). An agent planning in an environment shared with another updates beliefs both over the physical state and the other agents' models. In problems where we do not observe other's action explicitly but must infer it from sensing its effect on the state, observations are more informative about the other when the belief over the state space has reduced uncertainty. For typical, uncertain initial beliefs, we model the agent as if it were acting alone and utilize fast online planning for POMDPs. Subsequently, the agent switches to online planning in multiagent settings. We maintain tight lower and upper bounds at each step, and switch over when the difference between them reduces to less than ε.
@inproceedings{ijcai2013p61,
title = {Bimodal Switching for Online Planning in Multiagent Settings},
author = {Sonu, Ekhlas and Doshi, Prashant},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {360--365},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/61},
}
TY - CPAPER TI - Bimodal Switching for Online Planning in Multiagent Settings AU - Sonu, Ekhlas AU - Doshi, Prashant T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 360 EP - 365 UR - https://ijcai.org/proceedings/2013/61 ER -Copied
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