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Scientific Discovery : Computational Explorations of the Creative Processes

Scientific Discovery : Computational Explorations of the Creative Processes

Scientific Discovery : Computational Explorations of the Creative Processes
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Scientific Discovery : Computational Explorations of the Creative Processes Paperback - 1987

by Bradshaw, Gary L., Zytkow, Jan M., Simon, Herbert A., University of Chicago Staff, Langley, Pat

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MIT Press. Used - Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Details

  • Title Scientific Discovery : Computational Explorations of the Creative Processes
  • Author Bradshaw, Gary L., Zytkow, Jan M., Simon, Herbert A., University of Chicago Staff, Langley, Pat
  • Binding Paperback
  • Condition Used - Good
  • Pages 367
  • Volumes 1
  • Language ENG
  • Publisher MIT Press, Cambridge
  • Publication date February 24, 1987
  • Bookseller's Inventory # GRP97111284
  • ISBN 9780262620529 / 0262620529
  • Weight 1.29 lbs (0.59 kg)
  • Dimensions 9.01 x 5.93 x 0.85 in (22.89 x 15.06 x 2.16 cm)
  • Age range 18 to UP years
  • Grade levels 13 - UP
  • Category Computers - Other Applications
  • Library of Congress subjects Science, Creative ability in science
  • Library of Congress Catalogue Number 86010258
  • Dewey Decimal Code 502.8
  • Quantity available 1

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From the publisher

Scientific discovery is often regarded as romantic and creative--and hence unanalyzable--whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled.

Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought processes used to discover scientific laws. The programs--BACON, DALTON, GLAUBER, and STAHL--are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along.

Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science.

First line

A hypothesis that will be central to our inquiry is that the mechanisms of scientific discovery are not peculiar to that activity but can be subsumed as special cases of the general mechanisms of problem solving.

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