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Understanding Nonmodular Functionality: Lessons from Genetic Algorithms

Published online by Cambridge University Press:  01 January 2022

Jaakko Kuorikoski  and
Samuli Pöyhönen
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Abstract

Evolution is often characterized as a tinkerer creating efficient but messy solutions. We analyze the nature of the problems that arise when trying 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, first, that evolutionary designs are often hard to understand because they exhibit nonmodular functionality and, second, that breaches of modularity wreak havoc on our strategies of causal and constitutive explanation.

Type
General Philosophy of Science
Information
Philosophy of Science , Volume 80 , Issue 5 , December 2013 , pp. 637 - 649
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

†

The authors are listed in alphabetical order. Previous versions of this article were presented in the POS seminar and at the Models and Simulations 5 conference in Helsinki. We thank all the participants, as well as the audience at the PSA, for their valuable comments.

References

Bechtel, William, and Richardson, Robert C.. 2010. Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Clark, Andy. 1997. Being There: Putting Brain, Body and World Together Again. Cambridge, MA: MIT Press.Google Scholar
Clark, Andy 2001. Mindware: An Introduction to the Philosophy of Cognitive Science. Oxford: Oxford University Press.Google Scholar
Cummins, Robert. 1983. The Nature of Psychological Explanation. Cambridge, MA: MIT Press.Google Scholar
Goldberg, David E. 1989. Genetic Algorithms in Search Optimization and Machine Learning. Reading, MA: Addison-Wesley.Google Scholar
Holland, John. 1975. Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press.Google Scholar
Jacob, Francois. 1977. “Evolution and Tinkering.” Science 196 (4295): 1161–66..CrossRefGoogle ScholarPubMed
Kashtan, Nadav, and Alon, Uri. 2005. “Spontaneous Evolution of Modularity and Network Motifs.” Proceedings of the National Academy of Sciences of the USA 102 (39): 13773–78..CrossRefGoogle ScholarPubMed
Kashtan, Nadav, Noor, Elad, and Alon, Uri. 2007. “Varying Environments Can Speed Up Evolution.” Proceedings of the National Academy of Sciences of the USA 104 (34): 13711–16..CrossRefGoogle ScholarPubMed
Levins, Richard. 1973. “The Limits of Complexity.” In Hierarchy Theory: The Challenge of Complex Systems, ed. Pattee, Howard, 73–88. London: Braziller.Google Scholar
Marcus, Gary. 2008. Kluge: The Haphazard Construction of the Human Mind. Boston: Houghton Mifflin.Google Scholar
Mitchell, Melanie. 1996. An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press.Google Scholar
Mitchell, Melanie 2009. Complexity: A Guided Tour. Oxford: Oxford University Press.Google Scholar
Piccinini, Gualtiero, and Craver, Carl. 2011. “Integrating Psychology and Neuroscience: Functional Analyses as Mechanism Sketches.” Synthese 183 (3): 283–311..CrossRefGoogle Scholar
Pinker, Steven, and Prince, Alan. 1988. “On Language and Connectionism: Analysis of a Parallel Distributed Processing Model of Language Acquisition.” Cognition 23:73–193.CrossRefGoogle Scholar
Rumelhart, David, and McClelland, James. 1986. “On Learning the Past Tenses of English Verbs.” In Parallel Distributed Processing, Vol. 1, ed. McClelland, James, Rumelhart, David et al., 216–71. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Simon, Herbert. 1962. “The Architecture of Complexity.” Proceedings of the American Philosophical Society 106:476–82.Google Scholar
Wimsatt, William. 2007. Re-engineering Philosophy for Limited Beings. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar
Woodward, James. 2003. Making Things Happen. Oxford: Oxford University Press.Google Scholar
Ylikoski, Petri. 2009. “The Illusion of Depth of Understanding in Science.” In Scientific Understanding: Philosophical Perspectives, ed. Regt, Henk De, Leonelli, Sabine, and Eigner, Kai, 100–119. Pittsburgh: University of Pittsburgh Press.CrossRefGoogle Scholar
Ylikoski, Petri, and Kuorikoski, Jaakko. 2010. “Dissecting Explanatory Power.” Philosophical Studies 148:201–19.CrossRefGoogle Scholar