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ICCBR
2009
Springer
14 years 1 months ago
Improving Reinforcement Learning by Using Case Based Heuristics
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...
Reinaldo A. C. Bianchi, Raquel Ros, Ramon Ló...
CEEMAS
2005
Springer
14 years 28 days ago
Selection in Scale-Free Small World
Abstract. In this paper we compare our selection based learning algorithm with the reinforcement learning algorithm in Web crawlers. The task of the crawlers is to find new inform...
Zsolt Palotai, Csilla Farkas, András Lö...
IROS
2006
IEEE
190views Robotics» more  IROS 2006»
14 years 1 months ago
Q-RAN: A Constructive Reinforcement Learning Approach for Robot Behavior Learning
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
Jun Li, Achim J. Lilienthal, Tomás Mart&iac...
ICMLA
2010
13 years 5 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
ATAL
2005
Springer
14 years 28 days ago
Coordinated exploration in multi-agent reinforcement learning: an application to load-balancing
This paper is concerned with how multi-agent reinforcement learning algorithms can practically be applied to real-life problems. Recently, a new coordinated multi-agent exploratio...
Katja Verbeeck, Ann Nowé, Karl Tuyls