Balancing rotators with evolved neurocontrollers
Frank Pasemann, Ulf Dieckmann · 1997
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. submitted. International Institute for Applied Systems Analysis, ADN, A-2361 Laxenburg, Austria 1 Introduction The combined application of neural network techniques and evolutionary algorithms turned out to be a very effective tool for solving an interesting class of problems (for...