Author's personal copy CHAPTER ONE Toward a Unif ied Theory of Reasoning P. N. Johnson-Laird*,†,1, Sangeet S. Khemlani‡ *Department of Psychology, Princeton University, Princeton, NJ, USA †Department of Psychology, New York University, New York, NY, USA ‡Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC, USA 1Corresponding author: E-mail:
[email protected] Contents 1. Introduction 2 2. What Is Reasoning? 4 3. Models of Possibilities 6 4. Icons and Symbols 9 5. The Principle of Truth 11 6. Models as Counterexamples 13 7. Modulation and the Use of Knowledge 16 8. Induction and Abduction 20 9. Probabilities: Extensional and Intensional 23 10. Mental Simulations and Informal Programs 27 11. Toward a Uni!ed Theory 33 12. Conclusions 37 Acknowledgments 37 References 38 Abstract This article describes a theory that uses mental models to integrate deductive, induc- tive, and probabilistic reasoning. It spells out the main principles of the theory and illustrates them with examples from various domains. It shows how models underlie inductions, explanations, estimates of probabilities, and informal algorithms. In all these cases, a central principle is that the mind represents each sort of possibility in a separate mental model and infers whatever holds in the resulting set of models. Finally, the article reviews what has been accomplished in implementing the theory in a single large-scale computer program, mReasoner. Psychology of Learning and Motivation, Volume 59 © 2014 Elsevier Inc. ISSN 0079-7421, http://dx.doi.org/10.1016/B978-0-12-407187-2.00001-0 All rights reserved. 1 The Psychology of Learning and Motivation, First Edition, 2014, 1-42 Author's personal copy 2 P.