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JAIR
2008
107views more  JAIR 2008»
14 years 9 months ago
Planning with Durative Actions in Stochastic Domains
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
Mausam, Daniel S. Weld
QEST
2005
IEEE
15 years 3 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, ...
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
15 years 3 months ago
Convergence of stochastic search algorithms to gap-free pareto front approximations
Recently, a convergence proof of stochastic search algorithms toward finite size Pareto set approximations of continuous multi-objective optimization problems has been given. The...
Oliver Schütze, Marco Laumanns, Emilia Tantar...
PRL
2007
138views more  PRL 2007»
14 years 9 months ago
Ent-Boost: Boosting using entropy measures for robust object detection
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
Duy-Dinh Le, Shin'ichi Satoh
ECAI
2010
Springer
14 years 10 months ago
EP for Efficient Stochastic Control with Obstacles
Abstract. We address the problem of continuous stochastic optimal control in the presence of hard obstacles. Due to the non-smooth character of the obstacles, the traditional appro...
Thomas Mensink, Jakob J. Verbeek, Bert Kappen