Finding Approximate POMDP solutions Through Belief Compression
نویسندگان
چکیده
منابع مشابه
Finding Approximate POMDP solutions Through Belief Compression
Standard value function approaches to finding policies for Partially Observable Markov Decision Processes (POMDPs) are generally considered to be intractable for large models. The intractability of these algorithms is to a large extent a consequence of computing an exact, optimal policy over the entire belief space. However, in real-world POMDP problems, computing the optimal policy for the ful...
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Partially observable Markov decision process (POMDP) is a commonly adopted mathematical framework for solving planning problems in stochastic environments. However, computing the optimal policy of POMDP for large-scale problems is known to be intractable, where the high dimensionality of the underlying belief state space is one of the major causes. Our research focuses on studying two different...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 2005
ISSN: 1076-9757
DOI: 10.1613/jair.1496