publication . Part of book or chapter of book . Other literature type . 2006

Efficient non-linear control through neuroevolution

Gomez, Faustino; Schmidhuber, Jürgen; Miikkulainen, Risto;
Open Access
  • Published: 01 Jan 2006
  • Publisher: Springer Berlin Heidelberg
Abstract
Many complex control problems are not amenable to traditional controller design. Not only is it difficult to model real systems, but often it is unclear what kind of behavior is required. Reinforcement learning (RL) has made progress through direct interaction with the task environment, but it has been difficult to scale it up to large and partially observable state spaces. In recent years, neuroevolution, the artificial evolution of neural networks, has shown promise in tasks with these two properties. This paper introduces a novel neuroevolution method called CoSyNE that evolves networks at the level of weights. In the most extensive comparison of RL methods t...
Subjects
free text keywords: Cerebellar model articulation controller, Synaptic weight, Evolutionary algorithm, Computer science, Artificial intelligence, business.industry, business, Neuroevolution, Artificial neural network, Reinforcement learning, Nonlinear control, Information system
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Part of book or chapter of book
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http://dx.doi.org/10.1007/1187...
Other literature type . 2006
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Part of book or chapter of book
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