Part I. Introduction: 1. Introduction to computational cognitive modeling Ron Sun; Part II. Cognitive Modeling Paradigms: 2. Connectionist models of cognition Michael Thomas and James McClelland; 3. Bayesian models of cognition Thomas Griffiths, Charles Kemp, and Joshua Tenenbaum; 4. Dynamical systems approaches to cognition Gregor Schoener; 5. Declarative/ logic-based computational cognitive modeling Selmer Bringsjord; 6. Constraints in cognitive architectures Niels Taatgen and John Anderson; Part III. Computational Modeling of Various Cognitive Functionalities and Domains: 7. Computational models of episodic memory Kenneth Norman, Greg Detre, and Sean Polyn; 8. Computational models of semantic memory Timothy Rogers; 9. Models of categorization John Kruschke; 10. Micro-process models of decision making Jerome Busemeyer and Joseph Johnson; 11. Models of inductive reasoning Evan Heit; 12. Mental logic, mental models, and simulations of human deductive reasoning Philip Johnson-Laird and Yingrui Yang; 13. Computational models of skill acquisition Stellan Ohlsson; 14. Computational models of implicit learning Axel Cleeremans and Zoltan Dienes; 15. Computational models of attention and cognitive control Nicola De Pisapia, Grega Repov and Todd Braver; 16. Computational models of developmental psychology Thomas Shultz and Sylvain Sirois; 17. Computational models of psycholinguistics Nick Chater and Morten Christiansen; 18. Computational models in personality and social psychology Stephen Read and Brian Monroe; 19. Cognitive social simulation Ron Sun; 20. Models of scientific explanation Paul Thagard and Abninder Litt; 21. Cognitive modeling for cognitive engineering Wayne Gray; 22. Models of animal learning and their relations to human learning Francisco Lopez and David Shanks; 23. Computational modeling of visual information processing Pawan Sinha and Benjamin Balas; 24. Models of motor control Ferdinando Mussa-Ivaldi and Sara Solla; Part IV. Concluding Remarks: 25. An evaluation of computational modeling in cognitive science Margaret Boden; 26. Putting the pieces together again Aaron Sloman.

"[...] This edited volume by Sun (Rensselaer Polytechnic Institute) comprises two sections:[...] The first section will attract broader interest, especially from students, because of its juxtaposition of distinct approaches including connectionist, Bayesian, and logical modeling. The second section covers a range of topics, from memory and learning to decision making and cognitive control. [...] Given that the application chapters are largely independent of the methodological chapters, a dedicated instructor could cover more extensive ground by selecting primary papers on a desired topic. However, researchers who use computational approaches, or who want to become better consumers of computational psychology literature, may find this to be a valuable compilation of major ideas in this area. Recommended. --S.A. Huettel, Duke University CHOICE