Now showing items 1-3 of 3

  • Generating easy and hard problems using the Proximate Optimality Principle. [Dataset] 

    McCall, John; Christie, Lee A.; Brownlee, Alexander Edward Ian (OpenAIR@RGU, 2015-07-11)
    MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2015. Generating easy and hard problems using the Proximate Optimality Principle. [Dataset]. Held on OpenAIR [online]. Available from: https://hdl.handle.net/10059/1407
    These data were gathered to investigate the hypothesis that coherent functions will be easy and anti-coherent functions will be hard for a hillclimber. We generated 10 coherent functions for each length on bit-strings of ...
  • Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. 

    Christie, Lee A.; McCall, John; Lonie, David P. (ACM http://dx.doi.org/10.1145/2576768.2598240, 2014)
    CHRISTIE, L. A., MCCALL, J. A. W. and LONIE, D. P., 2014. Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. In: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation (GECCO '14). 12-16 July 2014. New York: ACM. pp. 333-340.
    Problem structure, or linkage, refers to the interaction between variables in a black-box fitness function. Discovering structure is a feature of a range of algorithms, including estimation of distribution algorithms (EDAs) ...
  • Partial structure learning by subset Walsh transform. 

    Christie, Lee A.; Lonie, David P.; McCall, John (IEEE http://dx.doi.org/10.1109/UKCI.2013.6651297, 2013)
    CHRISTIE, L. A., LONIE, D. P., and McCALL, J. A. W., 2013. Partial structure learning by subset Walsh transform. In: Proceedings of the 2013 UK Workshop on Computational Intelligence (UKCI), 2013. IEEE Press, pp. 128-135.
    Estimation of distribution algorithms (EDAs) use structure learning to build a statistical model of good solutions discovered so far, in an effort to discover better solutions. The non-zero coefficients of the Walsh ...