Resource-limited genetic programming: the dynamic approach

  • Authors:

  • Sara Silva;Ernesto Costa

  • Affiliations:

  • Centre for Informatics and Systems of the University of Coimbra, Coimbra, Portugal;Centre for Informatics and Systems of the University of Coimbra, Coimbra, Portugal

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

Resource-Limited Genetic Programming is a bloat control technique that imposes a single limit on the total amount of resources available to the entire population, where resources are tree nodes or code lines. We elaborate on this recent concept, introducing a dynamic approach to managing the amount of resources available for each generation. Initially low, this amount is increased only if it results in better population fitness. We compare the dynamic approach to the static method where a constant amount of resources is available throughout the run, and with the most traditional usage of a depth limit at the individual level. The dynamic approach does not impair performance on the Symbolic Regression of the quartic polynomial, and achieves excellent results on the Santa Fe Artificial Ant problem, obtaining the same fitness with only a small percentage of the computational effort demanded by the other techniques.