Bayesian models of cognition : reverse engineering the mind /
The definitive introduction to Bayesian cognitive science, written by pioneers of the field.How does human intelligence work, in engineering terms? How do our minds get so much from so little? Bayesian models of cognition provide a powerful framework for answering these questions by reverse-engineer...
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| Typ dokumentu: | Kniha |
| Jazyk: | Angličtina |
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Cambridge, Massachusetts :
The MIT Press,
[2024]
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| Témata: | |
| On-line přístup: | Elektronická verze přístupná pouze pro studenty a pracovníky MU |
| Příbuzné jednotky: | Tištěná verze::
Bayesian models of cognition |
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| 100 | 1 | |a Griffiths, Thomas L. |4 aut | |
| 245 | 1 | 0 | |a Bayesian models of cognition : |b reverse engineering the mind / |c Thomas L. Griffiths, Nick Chater, and Joshua B. Tenenbaum |
| 264 | 1 | |a Cambridge, Massachusetts : |b The MIT Press, |c [2024] | |
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| 505 | 0 | |a I, The Basics -- 1, Introduction the Bayesian approach to cognitive science -- 2, Probabilistic models of cognition in historical context -- 3, Bayesian inference -- 4, Graphical models -- 5, Building complex generative models -- 6, Approximate probabilistic inference -- 7, From probabilities to actions -- II, Advanced topics -- 8, Learning inductive bias with hierarchical Bayesian models -- 9, Capturing the growth of knowledge with nonparametric Bayesian models -- 10, Estimating subjective probability distributions -- 11, Sampling as a bridge across levels of analysis -- 12, Bayesian models and neutral networks -- 13, Resource-rational analysis -- 14, Theory of mind and inverse planning -- 15, Intuitive physics as probabilistic inference -- 16, Language processing and language learning -- 17, Bayesian inference over logical representations -- 18, Probabilistic programs as a unifying language of thought -- 19, Learning as Bayesian inference over programs -- 20, Bayesian models of cognitive development -- 21, The limits of inference and algorithmic probability -- 22, A Bayesian conversation | |
| 520 | 2 | 9 | |a The definitive introduction to Bayesian cognitive science, written by pioneers of the field.How does human intelligence work, in engineering terms? How do our minds get so much from so little? Bayesian models of cognition provide a powerful framework for answering these questions by reverse-engineering the mind. This textbook offers an authoritative introduction to Bayesian cognitive science and a unifying theoretical perspective on how the mind works. Part I provides an introduction to the key mathematical ideas and illustrations with examples from the psychological literature, including detailed derivations of specific models and references that can be used to learn more about the underlying principles. Part II details more advanced topics and their applications before engaging with critiques of the reverse-engineering approach. Written by experts at the forefront of new research, this comprehensive text brings the fields of cognitive science and artificial intelligence back together and establishes a firmly grounded mathematical and computational foundation for the understanding of human intelligence. The only textbook comprehensively introducing the Bayesian approach to cognitionWritten by pioneers in the fieldOffers cutting-edge coverage of Bayesian cognitive science's research frontiers Suitable for advanced undergraduate and graduate students and researchers across the sciences with an interest in the mind, brain, and intelligence Features short tutorials and case studies of specific Bayesian models. |9 eng |
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