Abstract
In a previous work we have reported on the evolutionary design optimisation of self-assembling Wang tiles. Apart from the achieved findings [11], nothing has been yet said about the effectiveness by which individuals were evaluated. In particular when the mapping from genotype to phenotype and from this to fitness is an intricate relationship. In this paper we aim to report whether our genetic algorithm, using morphological image analyses as fitness function, is an effective methodology. Thus, we present here fitness distance correlation to measure how effectively the fitness of an individual correlates to its genotypic distance to a known optimum when the genotype-phenotype-fitness mapping is a complex, stochastic and non-linear relationship.
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References
Altenberg, L.: Fitness Distance Correlation Analysis: An Instructive Counter example. In: 7th International Conference on Genetic Algorithms, pp. 57–64. Morgan Kaufmann, San Francisco (1997)
Jones, T.: Evolutionary algorithms, fitness landscapes and search. PhD thesis, University of New Mexico (1995)
Jones, T., Forrest, S.: Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms. In: 6th International Conference on Genetic Algorithms, pp. 184–192. Morgan Kaufmann Publishers Inc., San Francisco (1995)
Koljonen, J.: On fitness distance distributions and correlations, GA performance, and population size of fitness functions with translated optima. In: Honkela, T., Kortela, J., Raiko, T., Valpola, H. (eds.) 9th Scandinavian Conference on Artificial Intelligence, Finnish Artificial Intelligence Society, Espoo, Finland, pp. 68–74 (2006)
Li, L., Siepmann, P., Smaldon, J., Terrazas, G., Krasnogor, N.: Automated Self-Assembling Programming. In: Krasnogor, N., Gustafson, S., Pelta, D., Verdegay, J.L. (eds.) Systems Self-Assembly: Multidisciplinary Snapshots. Elsevier, Amsterdam (2008)
Michielsen, K., Raedt, H.D.: Morphological image analysis. Computer Physics Communications 1, 94–103 (2000)
Michielsen, K., Raedt, H.D.: Integral-geometry morphological image analysis. Physics Reports 347, 461–538 (2001), doi:10.1016/S0370-1573(00)00106-X
Quick, R.J., Rayward-Smith, V.J., Smith, G.D.: Fitness distance correlation and ridge functions. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 77–86. Springer, Heidelberg (1998)
Rothemund, P.W.K., Winfree, E.: The program-size complexity of self-assembled squares (extended abstract). In: 32nd ACM Symposium on Theory of computing, pp. 459–468. ACM, New York (2000), doi: http://doi.acm.org/10.1145/335305.335358
Terrazas, G., Krasnogor, N., Kendall, G., Gheorghe, M.: Automated Tile Design for Self-Assembly Conformations. In: IEEE Congress on Evolutionary Computation, vol. 2, pp. 1808–1814. IEEE Press, Los Alamitos (2005)
Terrazas, G., Gheorghe, M., Kendall, G., Krasnogor, N.: Evolving Tiles for Automated Self-Assembly Design. In: IEEE Congress on Evolutionary Computation, pp. 2001–2008. IEEE Press, Los Alamitos (2007)
Tomassini, M., Vanneschi, L., Collard, P., Clergue, M.: A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming. Evolutionary Computation 13(2), 213–239 (2005), doi: http://dx.doi.org/10.1162/1063656054088549
Vanneschi, L., Tomassini, M.: Pros and Cons of Fitness Distance Correlation in Genetic Programming. In: Barry, A.M. (ed.) Bird of a Feather Workshops, Genetic and Evolutionary Computation Conference, pp. 284–287. AAAI, Chigaco (2003)
Vanneschi, L., Tomassini, M., Collard, P., Clergue, M.: Fitness Distance Correlation in Structural Mutation Genetic Programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 455–464. Springer, Heidelberg (2003)
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Terrazas, G., Krasnogor, N. (2011). Genotype-Fitness Correlation Analysis for Evolutionary Design of Self-assembly Wang Tiles. In: Pelta, D.A., Krasnogor, N., Dumitrescu, D., Chira, C., Lung, R. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Studies in Computational Intelligence, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24094-2_5
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DOI: https://doi.org/10.1007/978-3-642-24094-2_5
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