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Speeding up learning with dynamic environment shaping in evolutionary robotics

Nicolas Bredeche 1, 2 Louis Hugues 3
1 TANC - Algorithmic number theory for cryptology
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
Abstract : Evolutionary Robotics is a promising approach to automatically build efficient controllers using stochastic optimization techniques. However, works in this area are often confronted to complex environments where even simple tasks cannot be achieved. In the scope of this paper, we propose an approach based on explicit problem decomposition and dynamic environment shaping to ease the learning task.
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Contributor : Nicolas Bredeche <>
Submitted on : Friday, September 28, 2007 - 2:34:12 PM
Last modification on : Thursday, March 18, 2021 - 3:54:19 PM
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  • HAL Id : inria-00175508, version 1



Nicolas Bredeche, Louis Hugues. Speeding up learning with dynamic environment shaping in evolutionary robotics. 5th International Workshop on Epigenetic Robotics, Jul 2005, Nara, Japan. p.128. ⟨inria-00175508⟩



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