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» Ensemble Algorithms in Reinforcement Learning
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159
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JCP
2007
143views more  JCP 2007»
15 years 4 months ago
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization
Abstract— We describe a general method to transform a non-Markovian sequential decision problem into a supervised learning problem using a K-bestpaths algorithm. We consider an a...
Nicolas Chapados, Yoshua Bengio
155
Voted
COLING
2002
15 years 4 months ago
Fine Grained Classification of Named Entities
While Named Entity extraction is useful in many natural language applications, the coarse categories that most NE extractors work with prove insufficient for complex applications ...
Michael Fleischman, Eduard H. Hovy
ROMAN
2007
IEEE
134views Robotics» more  ROMAN 2007»
15 years 10 months ago
Learning Reward Modalities for Human-Robot-Interaction in a Cooperative Training Task
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...
Anja Austermann, Seiji Yamada
AAMAS
2007
Springer
15 years 10 months ago
Networks of Learning Automata and Limiting Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
Peter Vrancx, Katja Verbeeck, Ann Nowé
156
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ATAL
2004
Springer
15 years 9 months ago
Learning User Preferences for Wireless Services Provisioning
The problem of interest is how to dynamically allocate wireless access services in a competitive market which implements a take-it-or-leave-it allocation mechanism. In this paper ...
George Lee, Steven Bauer, Peyman Faratin, John Wro...