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Finding Approximate POMDP solutions Through Belief Compression (2000)  (Make Corrections)  (8 citations)
Nicholas Roy Massachusetts Institute of Technology, Dept. of...



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Abstract: 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 full belief space is often unnecessary for good control even for problems with complicated policy... (Update)

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BibTeX entry:   (Update)

Nicholas Roy. Finding approximate POMDP solutions through belief compression. PhD Thesis Proposal, Carnegie Mellon University, 2000. http://citeseer.ist.psu.edu/roy00finding.html   More

@misc{ roy00finding,
  author = "N. Roy",
  title = "Finding approximate POMDP solutions through belief compression",
  text = "Nicholas Roy. Finding approximate POMDP solutions through belief compression.
    PhD Thesis Proposal, Carnegie Mellon University, 2000.",
  year = "2000",
  url = "citeseer.ist.psu.edu/roy00finding.html" }
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