Analog Genetic Encoding for the Evolution of Circuits and Networks
This paper describes a new kind of genetic representation called analog genetic encoding (AGE). The representation is aimed at the evolutionary synthesis and reverse engineering of circuits and networks such as analog electronic circuits, neural networks, and genetic regulatory networks. AGE permits the simultaneous evolution of the topology and sizing of the networks. The establishment of the links between the devices that form the network is based on an implicit definition of the interaction between different parts of the genome. This reduces the amount of information that must be carried by the genome relatively to a direct encoding of the links. The application of AGE is illustrated with examples of analog electronic circuit and neural network synthesis. The performance of the representation and the quality of the results obtained with AGE are compared with those produced by genetic programming.
Keywords: Evolutionary Computation ; Genetic Representation ; Analog Genetic Encoding ; AGE ; Analog Circuit Synthesis ; Analog Network Synthesis ; Genetic Representation ; Neural Network Synthesis ; AGE ; Analog Genetic Encoding ; Neuroevolution ; Implicit Encoding ; Implicit Genetic Encoding ; Genetic Representation ; AGE ; Analog Genetic Encoding ; Evolutionary Robotics
Record created on 2006-03-17, modified on 2016-08-08