A behavior-based analysis of modal problems

Conferences Papers
  1. Enrique Naredo and Leonardo Trujillo. Searching for Novel Clustering Programs. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation. 2013, 1093–1100. URL, DOI BibTeX

    	author = "Naredo, Enrique and Trujillo, Leonardo",
    	title = "Searching for Novel Clustering Programs",
    	booktitle = "Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation",
    	series = "GECCO '13",
    	year = 2013,
    	isbn = "978-1-4503-1963-8",
    	location = "Amsterdam, The Netherlands",
    	pages = "1093--1100",
    	numpages = 8,
    	url = "http://doi.acm.org/10.1145/2463372.2463505",
    	doi = "10.1145/2463372.2463505",
    	acmid = 2463505,
    	publisher = "ACM",
    	address = "New York, NY, USA",
    	keywords = "clustering, genetic programming, novelty search"

Genetic programming (GP) has proven to be a powerful tool for (semi)automated problem solving in various domains. However, while the algorithmic aspects of GP have been a primary object of study, there is a need to enhance the understanding of the problems where GP is applied. One particular goal is to categorize problems in a meaningful way, in order to select the best tools that can possibly be used to solve them. This paper studies modal problems, a conceptual class of problems recently proposed by Spector at GECCO 2012. Modal problems are those for which a solution program requires different modes of operation for different contexts. The thesis of this paper is that modality, in this sense, is better understood by analyzing program performance in behavioral space. The behavior-based perspective is seen as part of a scale of different forms of analyzing performance; with a coarse view given by a global fitness value and a highly detailed view provided by the semantics approach. On the other hand, behavioral analysis is seen as a flexible approach where the context of a program's performance is considered at in a domain-specific manner. The experimental evidence presented here suggests that behavior-based search could allow a GP to find programs with disjoint behavioral structures, that can satisfy the requirements of each mode of operation of a modal problem.

Published in
GECCO '13 Companion Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion
Volume 7835
Pages 1047-1054
Date of conference
03-05 Abril 2013
Last modified on%AM, %08 %230 %2013 %04:%Oct
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