Using mathematical programming to solve Factored Markov Decision Processes with Imprecise Probabilities
نویسندگان
چکیده
منابع مشابه
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 Fac...
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This paper investigates Factored Markov Decision Processes with Imprecise Probabilities; that is, Markov Decision Processes where transition probabilities are imprecisely specified, and where their specification does not deal directly with states, but rather with factored representations of states. We first define a Factored MDPIP, based on a multilinear formulation for MDPIPs; then we propose ...
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There are efficient solutions to planning problems modeled as a Markov Decision Process (MDP) envolving a reasonable number of states. However, known extensions of MDP are more suited to represent practical and more interesting applications, such as: (i) an MDP where states are represented by state variables, called a factored MDP; (ii) an MDP where probabilities are not completely known, calle...
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This paper presents a short survey of the research we have carried out on planning under uncertainty where we consider different forms of imprecision on the probability transition functions. Our main results are on efficient solutions for Markov Decision Process with Imprecise Transition Probabilities (MDP-IPs), a generalization of a Markov Decision Process where the imprecise probabilities are...
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We study languages that specify Markov Decision Processes with Imprecise Probabilities (MDPIPs) by mixing probabilities and logic programming. We propose a novel language that can capture MDPIPs and Markov Decision Processes with Set-valued Transitions (MDPSTs); we then obtain the complexity of one-step inference for the resulting MDPIPs and MDPSTs. We also present results of independent intere...
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ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2011
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2011.04.002