To view prices and purchase online, please login or create an account now.



Adaptationism and Optimality

Paperback / softback

Main Details

Title Adaptationism and Optimality
Authors and Contributors      Edited by Steven Hecht Orzack
Edited by Elliott Sober
SeriesCambridge Studies in Philosophy and Biology
Physical Properties
Format:Paperback / softback
Pages:424
Dimensions(mm): Height 229,Width 152
Category/GenrePhilosophy of science
Biology, life sciences
ISBN/Barcode 9780521598361
ClassificationsDewey:578.4
Audience
Professional & Vocational
Illustrations 6 Tables, unspecified; 2 Halftones, unspecified; 27 Line drawings, unspecified

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 4 June 2001
Publication Country United Kingdom

Description

The theory of adaptationism argues that natural selection contains sufficient explanatory power in itself to account for all evolution. However, there are differing views about the efficiency, or optimality, of the adaptation model of explanation. If the adaptationism theory is applied, are energy and resources being used as optimally as possible? Adaptationism and Optimality combines contributions from biologists and philosophers, and offers a systematic treatment of foundational, conceptual, and methodological issues surrounding the theory of adaptationism.

Author Biography

Elliott Sober is Hans Reichenbach Professor of Philosophy and William F. Vilas Research Professor at University of Wisconsin-Madison where he has taught since 1974. His research is in philosophy of science, especially in the philosophy of evolutionary biology. Sober's books include The Nature of Selection - Evolutionary Theory in Philosophical Focus (1984), Reconstructing the Past - Parsimony, Evolution, and Inference (1988), Philosophy of Biology (1993), From a Biological Point of View - Essays in Evolutionary Philosophy (1994), and Unto Others - The Evolution and Psychology of Unselfish Behavior (1998), coauthored with David Sloan Wilson.