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» Model Minimization in Markov Decision Processes
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FSTTCS
2006
Springer
14 years 11 days ago
Testing Probabilistic Equivalence Through Reinforcement Learning
We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
Josee Desharnais, François Laviolette, Sami...
STACS
1997
Springer
14 years 26 days ago
Methods and Applications of (MAX, +) Linear Algebra
Exotic semirings such as the “(max, +) semiring” (R ∪ {−∞}, max, +), or the “tropical semiring” (N ∪ {+∞}, min, +), have been invented and reinvented many times s...
Stephane Gaubert, Max Plus
EOR
2007
102views more  EOR 2007»
13 years 8 months ago
Sub-stochastic matrix analysis for bounds computation - Theoretical results
Performance evaluation of complex systems is a critical issue and bounds computation provides confidence about service quality, reliability, etc. of such systems. The stochastic ...
Serge Haddad, Patrice Moreaux
JSAC
2010
107views more  JSAC 2010»
13 years 7 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar
UAI
1997
13 years 10 months ago
Correlated Action Effects in Decision Theoretic Regression
Much recent research in decision theoretic planning has adopted Markov decision processes (MDPs) as the model of choice, and has attempted to make their solution more tractable by...
Craig Boutilier