Can Darwinian mechanisms make novel discoveries?: Learning from discoveries made by evolving neural networks [Book Review]

Foundations of Science 5 (2):225-238 (2000)
Abstract
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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Reprint years 2004
DOI 10.1023/A:1011356415685
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