Publications

The following are publications made possible by iCER resources. MSU faculty that would like to highlight the output of their research that's benefited from iCER resources are invited to contact us.

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J. Clune, Goldsby, H. J., Ofria, C., and Pennock, R. T., “Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory”, Proceedings of the Royal Society B: Biological Sciences, vol. 278, pp. 666-674, 2011.
J. Clune, Stanley, K. O., Pennock, R. T., and Ofria, C., “On the Performance of Indirect Encoding Across the Continuum of Regularity”, IEEE Transactions on Evolutionary Computation, 2011.
J. Clune, Beckmann, B. E., McKinley, P. K., and Ofria, C., “Investigating whether HyperNEAT produces modular neural networks”, in Proceedings of the Genetic and Evolutionary Computation Conference, 2010, pp. 635–642.
J. Clune, Ofria, C., and Pennock, R. T., “The sensitivity of HyperNEAT to different geometric representations of a problem”, in Proceedings of the Genetic and Evolutionary Computation Conference, 2009, pp. 675–682.
J. Clune, Beckmann, B. E., Ofria, C., and Pennock, R. T., “Evolving coordinated quadruped gaits with the HyperNEAT generative encoding”, in Proceedings of the IEEE Congress on Evolutionary Computation, 2009, pp. 2764-2771.
J. Clune, Beckmann, B. E., Pennock, R. T., and Ofria, C., “HybrID: A Hybridization of Indirect and Direct Encodings for Evolutionary Computation”, in Proceedings of the European Conference on Artificial Life, 2009.
J. Clune, Misevic, D., Ofria, C., Lenski, R. E., Elena, S. F., and Sanjuán, R., “Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes”, PLoS Computational Biology, vol. 4, p. e1000187, 2008.
J. Clune, Ofria, C., and Pennock, R. T., “How a generative encoding fares as problem-regularity decreases”, in Parallel Problem Solving from Nature, 2008, pp. 358–367.