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CDC
2010
IEEE
141views Control Systems» more  CDC 2010»
8 years 5 months ago
A dynamic programming algorithm for decentralized Markov decision processes with a broadcast structure
We give an optimal dynamic programming algorithm to solve a class of finite-horizon decentralized Markov decision processes (MDPs). We consider problems with a broadcast informati...
Jeff Wu, Sanjay Lall
QEST
2010
IEEE
8 years 8 months ago
Reasoning about MDPs as Transformers of Probability Distributions
We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
FMSD
2010
77views more  FMSD 2010»
8 years 8 months ago
A game-based abstraction-refinement framework for Markov decision processes
ASED ABSTRACTION-REFINEMENT FRAMEWORK FOR MARKOV DECISION PROCESSES Mark Kattenbelt Marta Kwiatkowska Gethin Norman David Parker CL-RR-08-06  Oxford University Computing Laborator...
Mark Kattenbelt, Marta Z. Kwiatkowska, Gethin Norm...
CORR
2010
Springer
105views Education» more  CORR 2010»
8 years 8 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
JAIR
2002
120views more  JAIR 2002»
8 years 9 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
ENTCS
2006
134views more  ENTCS 2006»
8 years 10 months ago
Partial Order Reduction for Probabilistic Branching Time
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
CORR
2006
Springer
113views Education» more  CORR 2006»
8 years 10 months ago
A Unified View of TD Algorithms; Introducing Full-Gradient TD and Equi-Gradient Descent TD
This paper addresses the issue of policy evaluation in Markov Decision Processes, using linear function approximation. It provides a unified view of algorithms such as TD(), LSTD()...
Manuel Loth, Philippe Preux
CORR
2008
Springer
154views Education» more  CORR 2008»
8 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
CORR
2008
Springer
91views Education» more  CORR 2008»
8 years 10 months ago
Significant Diagnostic Counterexamples in Probabilistic Model Checking
Abstract. This paper presents a novel technique for counterexample generation in probabilistic model checking of Markov chains and Markov Decision Processes. (Finite) paths in coun...
Miguel E. Andrés, Pedro R. D'Argenio, Peter...
CORR
2010
Springer
106views Education» more  CORR 2010»
8 years 10 months ago
MDPs with Unawareness
Markov decision processes (MDPs) are widely used for modeling decision-making problems in robotics, automated control, and economics. Traditional MDPs assume that the decision mak...
Joseph Y. Halpern, Nan Rong, Ashutosh Saxena
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