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Neural Networks and Q-Learning for Robotics

Abstract : Introduction Behavior-Based Approach Supervised Learning of a Behavior Miniature Mobile Robot Khepera Illustration: Reward-Penalty Learning Reinforcement Learning Genetic Algorithms Learning Classifier Systems GA & ANN Q-learning Evaluation Function Algorithm Reinforcement Function Update Function Convergence Limitations Generalization Neural Implementations of the Q-learning Multilayer Perceptron Implementation (ideal & Q-CON) Q-KOHON Comparison Knowledge Incorporation Reinforcement Function Design Building of a non-explicit Model Learning in Cooperative Robotics References
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https://hal-amu.archives-ouvertes.fr/hal-01355056
Contributor : Claude Touzet <>
Submitted on : Monday, August 22, 2016 - 5:35:43 PM
Last modification on : Monday, January 29, 2018 - 4:48:05 PM

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Claude Touzet. Neural Networks and Q-Learning for Robotics. IJCNN’99 (International Joint Conference (IEEE INNS) on Neural Networks), Jul 1999, Washington DC, United States. ⟨hal-01355056⟩

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