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SARA
2007
Springer
14 years 1 months ago
Active Learning of Dynamic Bayesian Networks in Markov Decision Processes
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Anders Jonsson, Andrew G. Barto
ICALP
2000
Springer
13 years 11 months ago
Temporal Rewards for Performance Evaluation
Today many formalisms exist for specifying complex Markov chains. In contrast, formalism for specifying the quantitative properties to analyze have remained quite primitive. In th...
Jeroen Voeten
CPC
2007
64views more  CPC 2007»
13 years 7 months ago
Sampling Regular Graphs and a Peer-to-Peer Network
d Abstract) Colin Cooper∗ , Martin Dyer† and Catherine Greenhill‡ We consider a simple Markov chain for d-regular graphs on n vertices, and show that the mixing time of this...
Colin Cooper, Martin E. Dyer, Catherine S. Greenhi...
INFOCOM
2010
IEEE
13 years 6 months ago
Markov Approximation for Combinatorial Network Optimization
—Many important network design problems can be formulated as a combinatorial optimization problem. A large number of such problems, however, cannot readily be tackled by distribu...
Minghua Chen, Soung Chang Liew, Ziyu Shao, Caihong...
LOGCOM
2010
87views more  LOGCOM 2010»
13 years 6 months ago
Exemplaric Expressivity of Modal Logics
Abstract This paper investigates expressivity of modal logics for transition systems, multitransition systems, Markov chains, and Markov processes, as coalgebras of the powerset, ï...
Bart Jacobs, Ana Sokolova