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Understanding non-modular functionality – lessons from genetic algorithms

Kuorikoski, Jaakko and Pöyhönen, Samuli (2012) Understanding non-modular functionality – lessons from genetic algorithms. In: [2012] Philosophy of Science Assoc. 23rd Biennial Mtg (San Diego, CA) > PSA 2012 Contributed Papers.

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    Abstract

    Evolution is often characterized as a tinkerer that creates efficient but messy solutions to problems. We analyze the nature of the problems that arise when we try to explain and understand cognitive phenomena created by this haphazard design process. We present a theory of explanation and understanding and apply it to a case problem – solutions generated by genetic algorithms. By analyzing the nature of solutions that genetic algorithms present to computational problems, we show that the reason for why evolutionary designs are often hard to understand is that they exhibit non-modular functionality, and that breaches of modularity wreak havoc on our strategies of causal and constitutive explanation.


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    Item Type: Conference or Workshop Item (UNSPECIFIED)
    Keywords: modularity; understanding; evolutionary algorithms; cognitive science
    Subjects: Specific Sciences > Cognitive Science
    General Issues > Explanation
    Conferences and Volumes: [2012] Philosophy of Science Assoc. 23rd Biennial Mtg (San Diego, CA) > PSA 2012 Contributed Papers
    Depositing User: Jaakko Kuorikoski
    Date Deposited: 16 Oct 2012 08:43
    Last Modified: 16 Oct 2012 08:43
    Item ID: 9373
    URI: http://philsci-archive.pitt.edu/id/eprint/9373

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