Optimal-design models and the strategy of model building in evolutionary biology

Philosophy of Science 47 (4):532-561 (1980)
  Copy   BIBTEX

Abstract

The prevalence of optimality models in the literature of evolutionary biology is testimony to their popularity and importance. Evolutionary biologist R. C. Lewontin, whose criticisms of optimality models are considered here, reflects that "optimality arguments have become extremely popular in the last fifteen years, and at present represent the dominant mode of thought." Although optimality models have received little attention in the philosophical literature, these models are very interesting from a philosophical point of view. As will be argued, optimality models are central to evolutionary thought, yet they are not readily accomodated by the traditional view of scientific theories. According to the traditional view, we would expect optimality models to employ general, empirical laws of nature, but they do not. Fortunately, the semantic view of scientific theories, a recent alternative to the traditional view, more readily accomodates optimality models. As we would expect on the semantic view, optimality models can be construed as specifications of ideal systems. These specifications may be used to describe empirical systems--that is, the specifications may have empirical instances. But the specifications are not empirical claims, much less general, empirical laws. Although philosophers have yet to discuss the general features and uses of optimality models, these topics have stimulated much recent discussion among evolutionary biologists. Their discussions raise a number of precautions concerning the proper use of optimality models. Moreover, many of their caveats can be interpreted as general reminders that 1) optimality models specify ideal systems whose empirical instantiations may be quite restricted, and that 2) optimality models should not be construed as general, empirical laws. As G. F. Oster and E. O. Wilson caution, "the prudent course is to regard optimality models as provisional guides to further empirical research and not necessarily as the key to deeper laws of nature." It seems, then, that the semantic view of theories is more sensitive to the nature and limitations of optimality models than is the more traditional view of theories

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 92,227

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

What’s Wrong with the Received View of Evolutionary Theory?John Beatty - 1980 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1980:397 - 426.
Optimality modeling and explanatory generality.Angela Potochnik - 2007 - Philosophy of Science 74 (5):680-691.
Optimization in Evolutionary Ecology.Robert C. Richardson - 1994 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:13 - 21.
Sub-optimal reasons for rejecting optimality.David R. Shanks & David Lagnado - 2000 - Behavioral and Brain Sciences 23 (5):761-762.
Models in biology.Jay Odenbaugh - 2009 - Routledge Encyclopedia of Philosophy.
Optimality modeling in a suboptimal world.Angela Potochnik - 2009 - Biology and Philosophy 24 (2):183-197.

Analytics

Added to PP
2009-01-28

Downloads
103 (#170,658)

6 months
29 (#108,432)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

John Beatty
University of British Columbia

References found in this work

The Logic of Scientific Discovery.Karl Popper - 1959 - Studia Logica 9:262-265.
Philosophy of Natural Science.Carl G. Hempel - 1967 - British Journal for the Philosophy of Science 18 (1):70-72.
The propensity interpretation of fitness.Susan K. Mills & John H. Beatty - 1979 - Philosophy of Science 46 (2):263-286.
Adaptation and Evolutionary Theory.Robert N. Brandon - 1978 - Studies in History and Philosophy of Science Part A 9 (3):181.

View all 13 references / Add more references