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» Representation Discovery for MDPs Using Bisimulation Metrics
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AAAI
2015
4 years 7 months ago
Representation Discovery for MDPs Using Bisimulation Metrics
We provide a novel, flexible, iterative refinement algorithm to automatically construct an approximate statespace representation for Markov Decision Processes (MDPs). Our approa...
Sherry Shanshan Ruan, Gheorghe Comanici, Prakash P...
AAAI
2010
10 years 2 days ago
Using Bisimulation for Policy Transfer in MDPs
Knowledge transfer has been suggested as a useful approach for solving large Markov Decision Processes. The main idea is to compute a decision-making policy in one environment and...
Pablo Samuel Castro, Doina Precup
AAAI
1997
9 years 12 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
BIBE
2006
IEEE
154views Bioinformatics» more  BIBE 2006»
10 years 4 months ago
Determining Molecular Similarity for Drug Discovery using the Wavelet Riemannian Metric
Discerning the similarity between two molecules is a challenging problem in drug discovery as well as in molecular biology. The importance of this problem is due to the fact that ...
Elinor Velasquez, Emmanuel R. Yera, Rahul Singh
ISPDC
2008
IEEE
10 years 5 months ago
Algorithms for Network Topology Discovery using End-to-End Measurements
Identifying and inferring performances of a network topology is a well known problem. Achieving this by using only end-to-end measurements at the application level is a method kno...
Laurent Bobelin, Traian Muntean
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