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- Daucé Emmanuel
- Dutech Alain
- AI
- Neural Control
- Reinforcement Learning
- Kernel Methods
COMM
We present a neural architecture which combines a new reinforcement learning algorithm with a topographic encoding of the inputs as inspired by kernel-based methods. This architecture is able to learn to control non-linear systems defined on a continuous space. Some results on a task of reaching are also given.