Can Darwinian mechanisms make novel discoveries?: Learning from discoveries made by evolving neural networks [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Foundations of Science 5 (2):225-238 (2000)
Some philosophers suggest that the development of scientificknowledge is a kind of Darwinian process. The process of discovery,however, is one problematic element of this analogy. I compare HerbertSimon's attempt to simulate scientific discovery in a computer programto recent connectionist models that were not designed for that purpose,but which provide useful cases to help evaluate this aspect of theanalogy. In contrast to the classic A.I. approach Simon used, ``neuralnetworks'' contain no explicit protocols, but are generic learningsystems built on the model of the interconnections of neurons in thebrain. I describe two cases that take the connectionist approach a stepfurther by using genetic algorithms, a form of evolutionary computationthat explicitly models Darwinian mechanisms. These cases show thatDarwinian mechanisms can make novel discoveries of complex, previouslyunknown patterns. With some caveats, they lend support to evolutionaryepistemology.
|Keywords||connectionism evolutionary epistemology genetic algorithms neural networks scientific discovery|
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Robert T. Pennock (2012). Negotiating Boundaries in the Definition of Life: Wittgensteinian and Darwinian Insights on Resolving Conceptual Border Conflicts. [REVIEW] Synthese 185 (1):5-20.
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