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QEST
2005
IEEE
13 years 10 months ago
An approximation algorithm for labelled Markov processes: towards realistic approximation
Abstract— Approximation techniques for labelled Markov processes on continuous state spaces were developed by Desharnais, Gupta, Jagadeesan and Panangaden. However, it has not be...
Alexandre Bouchard-Côté, Norm Ferns, ...
LICS
2003
IEEE
13 years 9 months ago
Labelled Markov Processes: Stronger and Faster Approximations
This paper reports on and discusses three notions of approximation for Labelled Markov Processes that have been developed last year. The three schemes are improvements over former...
Vincent Danos, Josee Desharnais
FOSSACS
2003
Springer
13 years 9 months ago
An Intrinsic Characterization of Approximate Probabilistic Bisimilarity
In previous work we have investigated a notion of approximate bisimilarity for labelled Markov processes. We argued that such a notion is more realistic and more feasible to compu...
Franck van Breugel, Michael W. Mislove, Joël ...
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 4 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
JAIR
2006
160views more  JAIR 2006»
13 years 4 months ago
Anytime Point-Based Approximations for Large POMDPs
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun