3051 search results - page 32 / 611 » Learning Internal Representations |
FLAIRS
2003
15 years 1 months ago
2003
This paper addresses the problem of improving the representation space in a rule-based intelligent system, through exception-based learning. Such a system generally learns rules c...
ICML
2008
IEEE
16 years 19 days ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
AIED
2009
Springer
15 years 6 months ago
2009
Springer
We describe a novel framework developed for transfer learning within reinforcement learning (RL) problems. Then we exhibit how this framework can be extended to intelligent tutorin...
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AAAI
2004
15 years 1 months ago
2004
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
GECCO
2006
Springer
15 years 3 months ago
2006
Springer
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...