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» Skill Combination for Reinforcement Learning
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AAAI
2006
15 years 1 months ago
On the Difficulty of Modular Reinforcement Learning for Real-World Partial Programming
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...
AAAI
1998
15 years 1 months ago
Applying Online Search Techniques to Continuous-State Reinforcement Learning
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...
Scott Davies, Andrew Y. Ng, Andrew W. Moore
ICML
2005
IEEE
16 years 18 days ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
CIVR
2007
Springer
15 years 6 months ago
Semantics reinforcement and fusion learning for multimedia streams
Fusion of multimedia streams for enhanced performance is a critical problem for retrieval. However, fusion performance tends to easily overfit the hillclimb set used to learn fus...
Dhiraj Joshi, Milind R. Naphade, Apostol Natsev
JMLR
2006
153views more  JMLR 2006»
14 years 11 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis