A virtual creatures model for studies in artificial evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Miconi:Avc:cec2005,

• author = "Thomas Miconi and Alastair Channon",
• title = "A virtual creatures model for studies in artificial evolution",
• booktitle = "Proceedings of the 2005 IEEE Congress on Evolutionary Computation",
• year = "2005",
• editor = "David Corne and Zbigniew Michalewicz and Bob McKay and Gusz Eiben and David Fogel and Carlos Fonseca and Garrison Greenwood and Gunther Raidl and Kay Chen Tan and Ali Zalzala",
• pages = "565--572",
• address = "Edinburgh, Scotland, UK",
• month = "2-5 " # sep,
• publisher = "IEEE Press",
• volume = "1",
• keywords = "genetic algorithms, genetic programming, ANN",
• ISBN = "0-7803-9363-5",
• URL = "http://www.channon.net/alastair/papers/cec2005.pdf",
• URL = "https://ieeexplore.ieee.org/document/1554733",
• URL = "http://ieeexplore.ieee.org/servlet/opac?punumber=10417&isvol=1",
• URL = "http://ieeexplore.ieee.org/servlet/opac?punumber=10417",
• DOI = "doi:10.1109/CEC.2005.1554733",
• size = "8 pages",
• abstract = "We present the results of our replication of Karl Sims' work on the evolution of artificial creatures in a physically realistic 3D environment. We used standard McCulloch-Pitts neurons instead of a more complex set of ad hoc neurons, which we believe makes our model a more general tool for future experiments in artificial (co-)evolution. We provide a detailed description of our model and freely accessible source code. We describe our results both qualitatively and quantitatively, including an analysis of some evolved neural controllers. To the best of our knowledge, our work is the first replication of Sims' efforts to achieve results comparable to Sims' in efficiency and complexity, with standard neurons and realistic Newtonian physics.",
• notes = "CEC2005 - A joint meeting of the IEEE, the IEE, and the EPS.",

}

Genetic Programming entries for Thomas Miconi Alastair D Channon

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