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» Ensemble Algorithms in Reinforcement Learning
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ILP
2007
Springer
15 years 10 months ago
Building Relational World Models for Reinforcement Learning
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...
GECCO
2006
Springer
171views Optimization» more  GECCO 2006»
15 years 8 months ago
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of classifiers. Genetic algorithm (GA) which uses the div...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
KDD
2010
ACM
282views Data Mining» more  KDD 2010»
15 years 8 months ago
Optimizing debt collections using constrained reinforcement learning
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....
IROS
2009
IEEE
154views Robotics» more  IROS 2009»
15 years 11 months ago
Consideration on robotic giant-swing motion generated by reinforcement learning
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
Masayuki Hara, Naoto Kawabe, Naoki Sakai, Jian Hua...
HPDC
2009
IEEE
15 years 8 months ago
Maestro: a self-organizing peer-to-peer dataflow framework using reinforcement learning
In this paper we describe Maestro, a dataflow computation framework for Ibis, our Java-based grid middleware. The novelty of Maestro is that it is a self-organizing peer-to-peer s...
C. van Reeuwijk