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Preferential attachment and the search for successful theories

Alexander, J. McKenzie (2013) Preferential attachment and the search for successful theories. Philosophy of Science, 80 (5). pp. 769-782. ISSN 0031-8248

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Identification Number: 10.1086/674080

Abstract

Multiarm bandit problems have been used to model the selection of competing scientific theories by boundedly rational agents. In this paper, I define a variable-arm bandit problem, which allows the set of scientific theories to vary over time. I show that Roth-Erev reinforcement learning, which solves multiarm bandit problems in the limit, cannot solve this problem in a reasonable time. However, social learning via preferential attachment combined with individual reinforcement learning which discounts the past, does.

Item Type: Article
Official URL: http://www.press.uchicago.edu/ucp/journals/journal...
Additional Information: © 2013 Philosophy of Science Association
Subjects: B Philosophy. Psychology. Religion > B Philosophy (General)
Q Science > Q Science (General)
Sets: Departments > Philosophy, Logic and Scientific Method
Date Deposited: 09 Aug 2012 07:29
Last Modified: 10 Feb 2014 12:27
URI: http://eprints.lse.ac.uk/id/eprint/45283

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