Analog Genetic Encoding for the Evolution of Circuits and Networks

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@Article{Mattiussi_2008_TEC,

• author = "Claudio Mattiussi and Dario Floreano",
• title = "Analog Genetic Encoding for the Evolution of Circuits and Networks",
• journal = "IEEE Transactions on Evolutionary Computation",
• year = "2007",
• volume = "11",
• number = "5",
• pages = "596--607",
• month = oct,
• keywords = "genetic algorithms, genetic programming, Analog circuit synthesis, analogue genetic encoding (AGE), analog network synthesis, evolutionary computation, genetic representation, neural network synthesis",
• ISSN = "1089-778X",
• DOI = "doi:10.1109/TEVC.2006.886801",
• size = "12 pages",
• abstract = "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 analogue 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.",

}

Genetic Programming entries for Claudio Mattiussi Dario Floreano

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