Depth-based short-sighted stochastic shortest path problems
نویسندگان
چکیده
منابع مشابه
Depth-based short-sighted stochastic shortest path problems
Stochastic Shortest Path Problems (SSPs) are a common representation for probabilistic planning problems. Two approaches can be used to solve SSPs: (i) consider all probabilistically reachable states and (ii) plan only for a subset of these reachable states. Closed policies, the solutions obtained in the former approach, require significant computational effort, and they do not require replanni...
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Algorithms to solve probabilistic planning problems can be classified in probabilistic planners and replanners. Probabilistic planners invest significant computational effort to generate a closed policy, i.e., a mapping function from every state to an action, and these solutions never “fail” if the problem correctly models the environment. Alternatively, replanners computes a partial policy, i....
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2014
ISSN: 0004-3702
DOI: 10.1016/j.artint.2014.07.001