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Abstract: We survey the complexity of computational problems about Markov decision processes: evaluating policies, finding good and best policies, approximating best policies, and related decision problems. 1 Introduction Partially-observable Markov decision processes (POMDPs) model sequential decision making when outcomes are uncertain and the state of the system cannot be completely observed. They consist of decision epochs, states, observations, actions, transition probabilities, and rewards. At... (Update)
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...case. The computational complexity of nite horizon control problems has received considerable attention recently, see for example [48,10,39,20]. For the in nitehorizon case, two questions, the complexity of goal state reachability with either nonzero probability or...
.... investigated the computational complexity of various MDP problems and algorithms [76, 13, 93, 84] A paper by Goldsmith and Mundhenk [45] surveys complexity results for many MDP problems and points to new directions. This thesis investigates questions raised in the rst...
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BibTeX entry: (Update)
Goldsmith, J., and Mundhenk, M. 1998. Complexity issues in Markov decision processes. In Proceedings of IEEE Conference on Computational Complexity, 272-- 280. http://citeseer.ist.psu.edu/goldsmith98complexity.html More
@inproceedings{ goldsmith98complexity,
author = "Judy Goldsmith and Martin Mundhenk",
title = "Complexity Issues in Markov Decision Processes",
booktitle = "{IEEE} Conference on Computational Complexity",
pages = "272-280",
year = "1998",
url = "citeseer.ist.psu.edu/goldsmith98complexity.html" }
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6 Encyclopaedia of complexity results for finite-horizon Marko.. - Mundhenk, Goldsmith et al. - 1997
6 The complexity of the policy existence problem for partially.. (context) - Mundhenk, Goldsmith et al. - 1997
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