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ICML
2010
IEEE
13 years 5 months ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
CORR
2008
Springer
85views Education» more  CORR 2008»
13 years 4 months ago
Feature Markov Decision Processes
Marcus Hutter
APN
2007
Springer
13 years 10 months ago
Markov Decision Petri Net and Markov Decision Well-Formed Net Formalisms
In this work, we propose two high-level formalisms, Markov Decision Petri Nets (MDPNs) and Markov Decision Well-formed Nets (MDWNs), useful for the modeling and analysis of distrib...
Marco Beccuti, Giuliana Franceschinis, Serge Hadda...
AIPS
2004
13 years 6 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht
HCI
2009
13 years 2 months ago
Partially Observable Markov Decision Process (POMDP) Technologies for Sign Language Based Human-Computer Interaction
Sign language (SL) recognition modules in human-computer interaction systems need to be both fast and reliable. In cases where multiple sets of features are extracted from the SL d...
Sylvie C. W. Ong, David Hsu, Wee Sun Lee, Hanna Ku...