Using mathematical programming to solve Factored Markov Decision Processes with Imprecise Probabilities
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]
|Collections||ANU Research Publications|
|Source:||International Journal of Approximate Reasoning|
|01_Delgado_Using_mathematical_programming_2011.pdf||555.64 kB||Adobe PDF||Request a copy|
|02_Delgado_Using_mathematical_programming_2011.pdf||309.86 kB||Adobe PDF||Request a copy|
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