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MiS Preprint

Balancing rotators with evolved neurocontrollers

Frank Pasemann and Ulf Dieckmann


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: Stabilize a rotating pendulum - that is mounted on a cart - in an upright position.

Dec 1, 1997
Dec 1, 1997

Related publications

1997 Repository Open Access
Frank Pasemann and Ulf Dieckmann

Evolved neurocontrollers for pole-balancing

In: Biological and artificial computation : from neuroscience to technology ; International Work-Conference on Artificial and Natural Neural Networks, IWANN'97 Lanzarote, Canary Islands, Spain, June 4-6, 1997 proceedings / José Mira (ed.)
Berlin : Springer, 1997. - pp. 1279-1287
(Lecture notes in computer science ; 1240)