Resolute Choice in Sequential Decision Problems with Multiple Priors
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2120-2124.
Abstract
This paper is devoted to sequential decision making under uncertainty, in the multi-prior framework of Gilboa and Schmeidler [1989]. In this setting, a set of probability measures (priors) is defined instead of a single one, and the decision maker selects a strategy that maximizes the minimum possible value of expected utility over this set of priors. We are interested here in the resolute choice approach, where one initially commits to a complete strategy and never deviates from it later. Given a decision tree representation with multiple priors, we study the problem of determining an optimal strategy from the root according to min expected utility. We prove the intractability of evaluating a strategy in the general case. We then identify different properties of a decision tree that enable to design dedicated resolution procedures. Finally, experimental results are presented that evaluate these procedures.
@inproceedings{ijcai2011p354,
title = {Resolute Choice in Sequential Decision Problems with Multiple Priors},
author = {Fargier, Helene and Jeantet, Gildas and Spanjaard, Olivier},
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 = {2120--2124},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-354},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-354},
}
TY - CPAPER TI - Resolute Choice in Sequential Decision Problems with Multiple Priors AU - Fargier, Helene AU - Jeantet, Gildas AU - Spanjaard, Olivier 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 - 2120 EP - 2124 DO - 10.5591/978-1-57735-516-8/IJCAI11-354 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-354 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: