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@inproceedings{1562536, author = {Chatterjee, Krishnendu and Elgyutt, Adrián and Novotný, Petr and Rouillé, Owen}, booktitle = {Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018)}, doi = {http://dx.doi.org/10.24963/ijcai.2018/652}, editor = {Jerome Lang}, keywords = {POMDPs; Planning under Uncertainty; Planning with Incomplete Information}, howpublished = {elektronická verze "online"}, isbn = {978-0-9992411-2-7}, pages = {4692--4699}, publisher = {ijcai.org}, title = {Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives}, year = {2018} }
TY - JOUR ID - 1562536 AU - Chatterjee, Krishnendu - Elgyutt, Adrián - Novotný, Petr - Rouillé, Owen PY - 2018 TI - Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives PB - ijcai.org SN - 9780999241127 KW - POMDPs KW - Planning under Uncertainty KW - Planning with Incomplete Information N2 - Partially-observable Markov decision processes (POMDPs) with discounted-sum payoff are a standard framework to model a wide range of problems related to decision making under uncertainty. Traditionally, the goal has been to obtain policies that optimize the expectation of the discounted-sum payoff. A key drawback of the expectation measure is that even low probability events with extreme payoff can significantly affect the expectation, and thus the obtained policies are not necessarily risk averse. An alternate approach is to optimize the probability that the payoff is above a certain threshold, which allows to obtain risk-averse policies, but ignore optimization of the expectation. We consider the expectation optimization with probabilistic guarantee (EOPG) problem where the goal is to optimize the expectation ensuring that the payoff is above a given threshold with at least a specified probability. We present several results on the EOPG problem, including the first algorithm to solve it. ER -
CHATTERJEE, Krishnendu, Adrián ELGYUTT, Petr NOVOTNÝ and Owen ROUILLÉ. Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives. Online. In Jerome Lang. \textit{Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018)}. ijcai.org, 2018, p.~4692--4699, 7 pp. ISBN~978-0-9992411-2-7. Available from: https://dx.doi.org/10.24963/ijcai.2018/652.
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