Jeff shrager (6 Ergebnisse)

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New.

, Shrager, Jeff, ed. Computational models of scientific discovery and theory formation. Edited by Jeff Shrager and Pat Langley. San Mateo, California: Morgan Kaufmann Publishers, 1990, xi, 498pp., very good dust-jacket, very good blue cloth. CONTENTS: 1. Computational approaches to scientific discovery / J. Shrager and P. Langley -- 2. The conceptual structure of the geological revolution / P. Thalgard and G. Nowak -- 3. On finding the most probable model / P. Cheeseman -- 4. An integrated approach to empirical discovery / B. Nordhausen and P. Langley -- 5. Deriving laws through analysis of processes and equations / J.M. Zytkow -- 6. A unified approach to explanation and theory formation / B. Falkenhainer -- 7. Theory formation by abduction: a case study based on the chemical revolution / P. O'Rouke, S. Morris, and D. Schulenburg -- 8. A computational approach to theory revision / S. Rajamoney -- 9. Experimentation in machine discovery / D. Kulkarni and H.A. Simon -- 10. Hypothesis formation as design / P.D. Karp. - 11. Diagnosing and fixing faults in theories / L. Darden -- 12. Designing good experiments to test bad hypotheses / D. Klahr, K. Dunbar, and A.L. Fay -- 13. Scientific discovery in the layperson / M.J. Pazzani and M. Flowers -- Compensation perception and the psychology of theory formation / J. Shrager -- 15. Five questions for computationalists / R.D. Tweney. 9781558601314 ISBN 1558601317.…

Hardcover. Zustand: Brand New. 1st edition. 352 pages. 10.50x7.25x1.00 inches. In Stock.

Zustand: New. Sarah Ciston is Professor of Computational Thinking and Aesthetic Doing at the Academy of Media Arts Cologne. Winner of the 2025 Ars Electronica STARTS Grand Prize, they are also the author of A Critical Field Guide for Working with Machine Learning Data.