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The challenge of irrationality: fractal protein recipes for PI

Published: 08 July 2009 Publication History

Abstract

Computational development traditionally focuses on the use of an iterative, generative mapping process from genotype to phenotype in order to obtain complex phenotypes which comprise regularity, repetition and module reuse. This work examines whether an evolutionary computational developmental algorithm is capable of producing a phenotype with no known pattern at all: the irrational number PI. The paper summarizes the fractal protein algorithm, provides a new analysis of how fractals are exploited by the developmental process, then presents experiments, results and analysis showing that evolution is capable of producing an approximate algorithm for PI that goes beyond the limits of precision of the data types used.

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Cited By

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  • (2013)GEARNetProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463490(973-980)Online publication date: 6-Jul-2013
  • (2012)Extracting key gene regulatory dynamics for the direct control of mechanical systemsProceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I10.1007/978-3-642-32937-1_47(468-477)Online publication date: 1-Sep-2012
  • (2011)On Synergistic Interactions Between Evolution, Development and Layered LearningIEEE Transactions on Evolutionary Computation10.1109/TEVC.2011.215075215:3(287-312)Online publication date: 1-Jun-2011
  • Show More Cited By

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    cover image ACM Conferences
    GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
    July 2009
    2036 pages
    ISBN:9781605583259
    DOI:10.1145/1569901
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 08 July 2009

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    Author Tags

    1. computational development
    2. evolutionary computation
    3. fractal proteins
    4. irrational numbers
    5. pattern
    6. pi

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    GECCO09
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    GECCO09: Genetic and Evolutionary Computation Conference
    July 8 - 12, 2009
    Québec, Montreal, Canada

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    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    Cited By

    View all
    • (2013)GEARNetProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463490(973-980)Online publication date: 6-Jul-2013
    • (2012)Extracting key gene regulatory dynamics for the direct control of mechanical systemsProceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I10.1007/978-3-642-32937-1_47(468-477)Online publication date: 1-Sep-2012
    • (2011)On Synergistic Interactions Between Evolution, Development and Layered LearningIEEE Transactions on Evolutionary Computation10.1109/TEVC.2011.215075215:3(287-312)Online publication date: 1-Jun-2011
    • (2010)Fractal gene regulatory networks for control of nonlinear systemsProceedings of the 11th international conference on Parallel problem solving from nature: Part II10.5555/1887255.1887279(209-218)Online publication date: 11-Sep-2010
    • (2010)Self modifying cartesian genetic programmingProceedings of the 12th annual conference on Genetic and evolutionary computation10.1145/1830483.1830591(579-586)Online publication date: 7-Jul-2010
    • (2010)Developments in Cartesian Genetic ProgrammingGenetic Programming and Evolvable Machines10.1007/s10710-010-9114-111:3-4(397-439)Online publication date: 1-Sep-2010
    • (2010)Fractal Gene Regulatory Networks for Control of Nonlinear SystemsParallel Problem Solving from Nature, PPSN XI10.1007/978-3-642-15871-1_22(209-218)Online publication date: 2010
    • (2009)A Multi-cellular Developmental Representation for Evolution of Adaptive Spiking Neural Microcircuits in an FPGAProceedings of the 2009 NASA/ESA Conference on Adaptive Hardware and Systems10.1109/AHS.2009.39(3-10)Online publication date: 29-Jul-2009

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