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Full Description
Intractability is a growing concern across the cognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-world complexity. Cognition and Intractability is the first book to provide an accessible introduction to computational complexity analysis and its application to questions of intractability in cognitive science. Covering both classical and parameterized complexity analysis, it introduces the mathematical concepts and proof techniques that can be used to test one's intuition of (in)tractability. It also describes how these tools can be applied to cognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy, cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an ideal resource for teaching or self-study.
Contents
Part I. Introduction: 1. Introduction; Part II. Concepts and Techniques: 2. Polynomial versus exponential time; 3. Polynomial-time reductions; 4. Classical complexity classes; 5. Fixed-parameter tractable time; 6. Parameterized reductions; 7. Parameterized complexity classes; Part III. Reflections and Elaborations: 8. Dealing with intractability; 9. Replies to common objections; Part IV. Applications: 10. Coherence as constraint satisfaction; 11. Analogy as structure mapping; 12. Communication as Bayesian inference.
