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15 years 5 months ago
Reinforcement Learning: An Introduction
"Reinforcement learning is learning what to do how to map situations to actions so as to maximize a numerical reward signal. The learner is not told which actions to take, as ...
Richard S. Sutton, Andrew G. Barto
ICRA
2009
IEEE
139views Robotics» more  ICRA 2009»
14 years 2 months ago
Transfer of knowledge for a climbing Virtual Human: A reinforcement learning approach
— In the reinforcement learning literature, transfer is the capability to reuse on a new problem what has been learnt from previous experiences on similar problems. Adapting tran...
Benoit Libeau, Alain Micaelli, Olivier Sigaud
ICCBR
2005
Springer
14 years 1 months ago
CBR for State Value Function Approximation in Reinforcement Learning
CBR is one of the techniques that can be applied to the task of approximating a function over high-dimensional, continuous spaces. In Reinforcement Learning systems a learning agen...
Thomas Gabel, Martin A. Riedmiller
CSEE
1999
Springer
13 years 11 months ago
Replacing a Hospital Information System: An Example of a Real-World Case Study
Real-world case studies are important to complement the academic skills and knowledge acquired by computer science students. In this paper we relate our experiences with a course ...
Klaas Sikkel, Ton A. M. Spil, Rob L. W. van de Weg
ROBOCUP
2005
Springer
134views Robotics» more  ROBOCUP 2005»
14 years 29 days ago
Simultaneous Learning to Acquire Competitive Behaviors in Multi-agent System Based on Modular Learning System
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments. A typical example is a case of RoboCup...
Yasutake Takahashi, Kazuhiro Edazawa, Kentarou Nom...