Computational Models of Scientific Discovery and Theory Formation

Abstract

1 Computational Approaches to Scientific Discovery, by Jeff Shrager and Pat Langley 2 The Conceptual Structure of the Geological Revolution, by Paul Thagard and Greg Nowak 3 On Finding the Most Probable Model, by Peter Cheeseman 4 An Integrated Approach to Empirical Discovery, by Bernd Nordhausen and Pat Langley 5 Deriving Laws Through Analysis of Processes and Equations, by Jan M. Zytkow 6. A Unified Approach to Explanation and Theory Formation, by Brian Falkenhainer 7 Theory Formation by Abduction: A Case Study Based on the Chemical Revolution, by Paul O'Rorke, Steven Morris, and David Schulenberg 8 A Computational Approach to Theory Revision, by Shankar Rajamoney 9 Experimentation in Machine Discovery, by Deepak Kulkarni and Herbert A. Simon 10. Hypothesis Formation As Design, by Peter D. Karp 11. Diagnosing and Fixing Faults in Theories, by Lindley Darden Appendix A Dale Moberg and John Josephson 12 Designing Good Experiments To Test Bad Hypotheses, by David Klahr, Kevin Dunbar, and Anne L. Fay 13. Scientific Discovery in the Layperson, by Michael J. Pazzani and Margot Flowers 14 Commonsense Perception and the Psychology of Theory Formation, by Jeff Shrager 15 Five Questions for Computationalists, by Ryan D. Tweney

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