The prospects for machine discovery in linguistics
Foundations of Science 4 (4):463-482 (1999)
| Abstract | The article reports the results from the developmentof four data-driven discovery systems, operating inlinguistics. The first mimics the induction methods ofJohn Stuart Mill, the second performs componentialanalysis of kinship vocabularies, the third is ageneral multi-class discrimination program, and thefourth finds logical patterns in data. These systemsare briefly described and some arguments are offeredin favour of machine linguistic discovery. Thearguments refer to the strength of machines incomputationally complex tasks, the guaranteedconsistency of machine results, the portability ofmachine methods to new tasks and domains, and thepotential machines provide for our gaining newinsights. | |||||||||
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Mario Alai (2004). A.I., Scientific Discovery and Realism. Minds and Machines 14 (1):21-42.
E. E. Vityaev & B. Y. Kovalerchuk (2004). Discovery of Empirical Theories Based on the Measurement Theory. Minds and Machines 14 (4):551-573.
J. Storrs Hall (2006). Nano-Enabled AI. International Journal of Applied Philosophy 20 (2):247-261.
Herbert Simon (1995). Machine Discovery. Foundations of Science 1 (2).
Jan M. Zytkow & Herbert A. Simon (1988). Normative Systems of Discovery and Logic of Search. Synthese 74 (1):65 - 90.
Francesco Amigoni, Viola Schiaffonati & Marco Somalvico (2000). A Multilevel Architecture of Creative Dynamic Agency. Foundations of Science 5 (2):157-184.
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