CHATTERJEE, Krishnendu, Adrián ELGYUTT, Petr NOVOTNÝ and Owen ROUILLÉ. Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives. Online. In Jerome Lang. 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.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives
Authors CHATTERJEE, Krishnendu, Adrián ELGYUTT, Petr NOVOTNÝ and Owen ROUILLÉ.
Edition Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), p. 4692--4699, 7 pp. 2018.
Publisher ijcai.org
Other information
Type of outcome Proceedings paper
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
ISBN 978-0-9992411-2-7
Doi http://dx.doi.org/10.24963/ijcai.2018/652
Keywords in English POMDPs; Planning under Uncertainty; Planning with Incomplete Information
Tags International impact, Reviewed
Changed by Changed by: doc. RNDr. Petr Novotný, Ph.D., učo 172743. Changed: 26/9/2019 10:15.
Abstract
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.
PrintDisplayed: 20/7/2024 04:53