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    » Parametric regret in uncertain Markov decision processes
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    AI
    2008
    Springer
    123views Artificial Intelligence» more  AI 2008»
    Reachability analysis of uncertain systems using bounded-parameter Markov decision processes
    13 years 5 months ago
    Reachability analysis of uncertain systems using bounded-parameter Markov decision processes
    Download  www.vuse.vanderbilt.edu
    Verification of reachability properties for probabilistic systems is usually based on variants of Markov processes. Current methods assume an exact model of the dynamic behavior a...
    Di Wu, Xenofon D. Koutsoukos
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    FSS
    2006
    84views more  FSS 2006»
    A fuzzy approach to Markov decision processes with uncertain transition probabilities
    13 years 4 months ago
    A fuzzy approach to Markov decision processes with uncertain transition probabilities
    Download  www.math.s.chiba-u.ac.jp
    M. Kurano, M. Yasuda, J. Nakagami, Y. Yoshida
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    NFM
    2011
    225views Formal Methods» more  NFM 2011»
    Synthesis for PCTL in Parametric Markov Decision Processes
    12 years 12 months ago
    Synthesis for PCTL in Parametric Markov Decision Processes
    Download  www.veriware.org
    Abstract. In parametric Markov Decision Processes (PMDPs), transition probabilities are not fixed, but are given as functions over a set of parameters. A PMDP denotes a family of ...
    Ernst Moritz Hahn, Tingting Han, Lijun Zhang
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    NIPS
    2004
    103views Information Technology» more  NIPS 2004»
    Experts in a Markov Decision Process
    13 years 6 months ago
    Experts in a Markov Decision Process
    Download  books.nips.cc
    We consider an MDP setting in which the reward function is allowed to change during each time step of play (possibly in an adversarial manner), yet the dynamics remain fixed. Simi...
    Eyal Even-Dar, Sham M. Kakade, Yishay Mansour
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    ECML
    2005
    Springer
    143views Machine Learning» more  ECML 2005»
    Active Learning in Partially Observable Markov Decision Processes
    13 years 10 months ago
    Active Learning in Partially Observable Markov Decision Processes
    Download  www.cs.mcgill.ca
    This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
    Robin Jaulmes, Joelle Pineau, Doina Precup
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