Natural methods for robot task learning: instructive demonstrations, generalization and practice
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Introducing long term memory in an ANN based multilevel darwinist brain
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
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In this paper we present a strategy for inducing a behavior in a real agent through a learning process with a human teacher. The agent creates internal models extracting information from the consequences of the actions it must carry out, and not just learning the task itself. The mechanism that permits this background learning process is the Multilevel Darwinist Brain, a cognitive mechanism that allows an autonomous agent to decide the actions it must apply in its environment in order to fulfill its motivations. It is a reinforcement based mechanism that uses evolutionary techniques to perform the on line learning of the models.