Overview of Linear Program Approximations for Factored Continuous and Hybrid-State Markov Decision Processes
نویسنده
چکیده
Approximate linear programming (ALP) is as one of the most promising methods for solving complex factored MDPs. The method was applied first to tackle problems with discrete state variables. More recently the ALP methods that can solve MDPs with continuous and hybrid (both continuous and discrete) variables have emerged. This paper briefly reviews the work on ALP methods for such problems.
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