Automated Extraction of Problem Structure

  • Anthony Bucci
  • Jordan B. Pollack
  • Edwin de Jong
Conference paper

DOI: 10.1007/978-3-540-24854-5_53

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3102)
Cite this paper as:
Bucci A., Pollack J.B., de Jong E. (2004) Automated Extraction of Problem Structure. In: Deb K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg

Abstract

Most problems studied in artificial intelligence possess some form of structure, but a precise way to define such structure is so far lacking. We investigate how the notion of problem structure can be made precise, and propose a formal definition of problem structure. The definition is applicable to problems in which the quality of candidate solutions is evaluated by means of a series of tests. This specifies a wide range of problems: tests can be examples in classification, test sequences for a sorting network, or opponents for board games. Based on our definition of problem structure, we provide an automatic procedure for problem structure extraction, and results of proof-of-concept experiments. The definition of problem structure assigns a precise meaning to the notion of the underlying objectives of a problem, a concept which has been used to explain how one can evaluate individuals in a coevolutionary setting. The ability to analyze and represent problem structure may yield new insight into existing problems, and benefit the design of algorithms for learning and search.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Anthony Bucci
    • 1
  • Jordan B. Pollack
    • 1
  • Edwin de Jong
    • 2
  1. 1.DEMO LabBrandeis UniversityWalthamUSA
  2. 2.Decision Support Systems GroupUniversiteit Utrecht 

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