Approximate Linear Programming for Solving Hybrid Factored MDPs
نویسنده
چکیده
Hybrid approximate linear programming (HALP) has recently emerged as a promising approach to solving large factored Markov decision processes (MDPs) with discrete and continuous state and action variables. Its central idea is to reformulate initially intractable problem of computing the optimal value function as its linear programming approximation. In this work, we present the HALP framework and discuss several representational and computational issues that make the approach appropriate for large MDPs. We compare three different methods for solving HALP and demonstrate the feasibility of the approach on high-dimensional distributed control problems.
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