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A probabilistic database approach to the analysis of genetic algorithms

  • Theoretical Foundations of Evolutionary Computation
  • Conference paper
  • First Online:
Parallel Problem Solving from Nature — PPSN IV (PPSN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1141))

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Abstract

This paper takes a fresh look at some of the key ideas of genetic algorithms, using concepts drawn from the theory of majorization and probabilistic databases. We show the intimate relationships between GAs and the theory of probabilistic databases. We show how deception is well described using Saari's theorem, and its relationships with the Simpson and other paradoxes in decision theory. Reconstructability, a concept of fundamental importance in databases, is proposed as a useful substitute for deception. The database projection operator is connected with hyperplane partitions, and is used to show the nexus between point crossover operators and the join operator. Using results from probabilistic databases, we show that crossover may be considered as a majorization operator.

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Author information

Authors and Affiliations

  1. School of Computer & Information Science, 2-120 Center for Science and Technology, Syracuse University, 13244, Syracuse, NY

    Anil Menon, Kishan Mehrotra & Chilukuri K. Mohan

  2. Department of CISE, University of Florida, 301 CSE Bldg, 32611, Gainesville, FL

    Sanjay Ranka

Authors
  1. Anil Menon
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  2. Kishan Mehrotra
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  3. Chilukuri K. Mohan
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  4. Sanjay Ranka
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Editor information

Hans-Michael Voigt Werner Ebeling Ingo Rechenberg Hans-Paul Schwefel

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© 1996 Springer-Verlag Berlin Heidelberg

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Menon, A., Mehrotra, K., Mohan, C.K., Ranka, S. (1996). A probabilistic database approach to the analysis of genetic algorithms. In: Voigt, HM., Ebeling, W., Rechenberg, I., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN IV. PPSN 1996. Lecture Notes in Computer Science, vol 1141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61723-X_980

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  • DOI: https://doi.org/10.1007/3-540-61723-X_980

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61723-5

  • Online ISBN: 978-3-540-70668-7

  • eBook Packages: Springer Book Archive

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