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GECCO
2011
Springer
14 years 1 months ago
2011
Springer
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
ECML
1997
Springer
15 years 2 months ago
1997
Springer
In learning from examples it is often useful to expand an attribute-vector representation by intermediate concepts. The usual advantage of such structuring of the learning problemi...
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...
ESANN
2001
14 years 11 months ago
2001
This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
ML
2006
ACM
14 years 10 months ago
2006
ACM
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...