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144
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GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
15 years 9 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
190
Voted
AGENTS
2001
Springer
15 years 8 months ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
133
Voted
SAGA
2001
Springer
15 years 8 months ago
Stochastic Finite Learning
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...
Thomas Zeugmann
137
Voted
CG
2000
Springer
15 years 8 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
117
Voted
ICML
2007
IEEE
16 years 4 months ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu