Evolving structure and function of neurocontrollers

Pasemann F, Steinmetz U, & Dieckmann U (1999). Evolving structure and function of neurocontrollers. In: CEC 99: Proceedings of the 1999 Congress on Evolutionary Computation, 6-9 July 1999.

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Abstract

The presented evolutionary algorithm is especially designed to generate recurrent neural networks with non-trivial internal dynamics. It is not based on genetic algorithms, and sets no constraints on the number of neurons and the architecture of a network. Network topology and parameters like synaptic weights and bias terms are developed simultaneously. It is well suited for generating neuromodules acting in sensorimotor loops, and therefore it can be used for evolution of neurocontrollers solving also nonlinear control problems. We demonstrate this capability by applying the algorithm successfully to the following task: a rotating pendulum is mounted on a cart; stabilize the rotator in an upright position, and center the cart in a given finite interval...

Item Type: Conference or Workshop Item (UNSPECIFIED)
Research Programs: Adaptive Dynamics Network (ADN)
Bibliographic Reference: In:; CEC 99: Proceedings of the 1999 Congress on Evolutionary Computation; 6-9 July 1999, Washington, DC, USA
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:11
Last Modified: 20 Jan 2016 16:41
URI: http://pure.iiasa.ac.at/5849

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