Mattiussi, ClaudioFloreano, Dario2006-01-122006-01-122006-01-122004https://infoscience.epfl.ch/handle/20.500.14299/221618WOS:000222965600004We introduce and apply a genetic representation for analog electronic circuits based on the association of character strings extracted from the genome with the ter-minals and parameters of components, and the use of local string alignment to generate the connection between components. The representation produces a variable ge-nome length structure that tolerates the execution of ma-jor genome reorganization operators such as duplication and transposition, along with less disruptive ones such as character insertion, deletion and substitution. The repre-sentation can be applied also to other analog networks such as artificial neural networks, control systems, and biological genetic regulatory networks.AGEAnalog Genetic EncodingNeuroevolutionNeuromodulationEvolution of Analog Electronic CircuitsReinforcement LearningImplicit EncodingImplicit Genetic EncodingEvolutionary Roboticstext::conference output::conference proceedings::conference paper