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UAI
2000
14 years 11 months ago
The Complexity of Decentralized Control of Markov Decision Processes
We consider decentralized control of Markov decision processes and give complexity bounds on the worst-case running time for algorithms that find optimal solutions. Generalization...
Daniel S. Bernstein, Shlomo Zilberstein, Neil Imme...
NFM
2011
225views Formal Methods» more  NFM 2011»
14 years 4 months ago
Synthesis for PCTL in Parametric Markov Decision Processes
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
MDAI
2005
Springer
15 years 3 months ago
Perceptive Evaluation for the Optimal Discounted Reward in Markov Decision Processes
We formulate a fuzzy perceptive model for Markov decision processes with discounted payoff in which the perception for transition probabilities is described by fuzzy sets. Our aim...
Masami Kurano, Masami Yasuda, Jun-ichi Nakagami, Y...
AIPS
2011
14 years 1 months ago
Sample-Based Planning for Continuous Action Markov Decision Processes
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
CORR
2008
Springer
154views Education» more  CORR 2008»
14 years 10 months ago
A Counterexample Guided Abstraction-Refinement Framework for Markov Decision Processes
rexample Guided Abstraction-Refinement Framework for Markov Decision Processes ROHIT CHADHA and MAHESH VISWANATHAN Dept. of Computer Science, University of Illinois at Urbana-Champ...
Rohit Chadha, Mahesh Viswanathan