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Efficient solutions to factored MDPs with imprecise transition probabilities

Delgado, Karina Valdivia; Sanner, Scott; De Barros, Leliane Nunes


When modeling real-world decision-theoretic planning problems in the Markov Decision Process (MDP) framework, it is often impossible to obtain a completely accurate estimate of transition probabilities. For example, natural uncertainty arises in the transition specification due to elicitation of MDP transition models from an expert or estimation from data, or non-stationary transition distributions arising from insufficient state knowledge. In the interest of obtaining the most robust policy...[Show more]

CollectionsANU Research Publications
Date published: 2011
Type: Journal article
Source: Artificial Intelligence
DOI: 10.1016/j.artint.2011.01.001


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