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"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 ...
ICRA
2009
IEEE
15 years 4 months ago
2009
IEEE
— 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...
ICCBR
2005
Springer
15 years 3 months ago
2005
Springer
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...
CSEE
1999
Springer
15 years 2 months ago
1999
Springer
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 ...
ROBOCUP
2005
Springer
15 years 3 months ago
2005
Springer
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...