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» Compositionality for Markov Reward Chains with Fast Transiti...
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TWC
2008
130views more  TWC 2008»
13 years 7 months ago
On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance
We consider a multi-channel opportunistic communication system where the states of these channels evolve as independent and statistically identical Markov chains (the Gilbert-Elli...
Qing Zhao, Bhaskar Krishnamachari, Keqin Liu
UAI
2000
13 years 9 months ago
Fast Planning in Stochastic Games
Stochastic games generalize Markov decision processes MDPs to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards de...
Michael J. Kearns, Yishay Mansour, Satinder P. Sin...
AMAI
2006
Springer
13 years 7 months ago
Symmetric approximate linear programming for factored MDPs with application to constrained problems
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
Dmitri A. Dolgov, Edmund H. Durfee
ATVA
2010
Springer
135views Hardware» more  ATVA 2010»
13 years 8 months ago
Probabilistic Contracts for Component-Based Design
Abstract. We define a probabilistic contract framework for the construction of component-based embedded systems, based on the theory of Interactive Markov Chains. A contract specif...
Dana N. Xu, Gregor Gößler, Alain Giraul...
SIGMETRICS
2000
ACM
105views Hardware» more  SIGMETRICS 2000»
13 years 12 months ago
Using the exact state space of a Markov model to compute approximate stationary measures
We present a new approximation algorithm based on an exact representation of the state space S, using decision diagrams, and of the transition rate matrix R, using Kronecker algeb...
Andrew S. Miner, Gianfranco Ciardo, Susanna Donate...