Value-Function Approximations for Partially Observable Markov Decision Processes
نویسندگان
چکیده
منابع مشابه
Value-Function Approximations for Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in which states of the system are observable only indirectly, via a set of imperfect or noisy observations. The modeling advantage of POMDPs, however, comes at a price — exact methods for solving them are computationally very...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2000
ISSN: 1076-9757
DOI: 10.1613/jair.678