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Using mathematical programming to solve Factored Markov Decision Processes with Imprecise Probabilities

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

Description

This paper investigates Factored Markov Decision Processes with Imprecise Probabilities (MDPIPs); that is, Factored Markov Decision Processes (MDPs) where transition probabilities are imprecisely specified. We derive efficient approximate solutions for Factored MDPIPs based on mathematical programming. To do this, we extend previous linear programming approaches for linear approximations in Factored MDPs, resulting in a multilinear formulation for robust "maximin" linear approximations in...[Show more]

CollectionsANU Research Publications
Date published: 2011
Type: Journal article
URI: http://hdl.handle.net/1885/68138
Source: International Journal of Approximate Reasoning
DOI: 10.1016/j.ijar.2011.04.002

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