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020 ▼a 9780262346313 ▼q (electronic bk.)
020 ▼a 0262346311 ▼q (electronic bk.)
020 ▼z 9780262037860 ▼q (print)
035 ▼a 1845057 ▼b (N$T)
035 ▼a (OCoLC)1035389940
037 ▼a 11400 ▼b MIT Press
040 ▼a MITPR ▼b eng ▼e rda ▼e pn ▼c MITPR ▼d OCLCF ▼d YDX ▼d P@U ▼d EBLCP ▼d N$T ▼d 248032
049 ▼a MAIN
050 4 ▼a P142 ▼b .K26 2018eb
072 7 ▼a LAN ▼x 000000 ▼2 bisacsh
08204 ▼a 401/.9 ▼2 23
1001 ▼a Kapatsinski, Vsevolod, ▼e author.
24510 ▼a Changing minds changing tools : ▼b from learning theory to language acquisition to language change / ▼c Vsevolod Kapatsinski. ▼h [electronic resource]
260 1 ▼a Cambridge : ▼b The MIT Press, ▼c 2018.
300 ▼a 1 online resource (392 pages)
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a computer ▼b c ▼2 rdamedia
338 ▼a online resource ▼b cr ▼2 rdacarrier
504 ▼a Includes bibliographical references and index.
5050 ▼a Intro; Contents; Acknowledgments; Introduction; Explaining Language by Explaining Language Change; On Innateness, Learning, and Learning Mechanisms; The Structure of This Book; 1 The Web in the Spider: Associative Learning Theory; 1.1 Associationist Learning Mechanisms: Hebbian and Error-Driven Learning; 1.2 Associative Symmetry and Chunking; 1.3 Setting Up the Problem: A Role for Cognitive Control; 1.4 Node Properties: Attention, Associability, Accessibility; 1.5 What Is a Domain-General Learning Mechanism Anyway?; 1.6 Why Associationism?; 1.7 Sources of Bias; 1.8 Conclusion and Preview
5058 ▼a 2 From Associative Learning to Language Structure2.1 What We Can vs. What We Want; 2.2 When Hell Freezes Over; 2.3 What Is to Be Learned?; 2.4 Directionality; 2.5 Specificity; 2.6 Conclusion and Preview; 3 What Are the Nodes? Unitization and Configural Learning vs. Selective Attention; 3.1 Elements and Configurations; 3.2 What Makes Units Fuse?; 3.3 Part-Whole Interactions in Learning: Hierarchical Inference; 3.4 Occasion Setting and Cue-Outcome Fusion; 3.5 Incremental Processing and Loss of Configurality; 3.6 Elemental Comprehension; 3.7 Determinants of Attention; 3.8 Learning to Attend
5058 ▼a 3.9 Learning to Ignore3.10 Mediation: An Open Field; 3.11 Conclusion; 4 Bayes, Rationality, and Rashionality; 4.1 Confidence; 4.2 Entrenchment and Suspicious Coincidence; 4.3 Learned Inattention; 4.4 Exoneration and Holmesian Inference; 4.5 Outcome Competition as Covert Cue Competition; 4.6 Active Learning: What Do We Seek?; 4.7 Generative vs. Discriminative Models; 4.8 Conclusion; 5 Continuous Dimensions and Distributional Learning; 5.1 Dimensions; 5.2 Within-Category Variability and Extrapolation; 5.3 Distributions and Distributional Learning
5058 ▼a 5.4 The Mechanisms behind Distributional Learning5.5 Salience of the Unexpected in Distributional Learning; 5.6 The Role of Prediction Error in Learning a Distribution; 5.7 Salience of the Unexpected and Regions of Perceptual Equivalence; 5.8 Some Alternative Explanations for Flat Tops; 5.9 Conclusion; 6 Schematic Structure, Hebbian Learning, and Semantic Change; 6.1 Semantic Change in Grammaticalization; 6.2 Semantic Extension vs. Entrenchment; 6.3 The Experiment; 6.4 A Hebbian Learning Model; 6.5 Conclusion; 7 Learning Paradigmatic Structure; 7.1 Associationist Theories of Paradigm Learning
5058 ▼a 7.2 Competition in Production7.3 Interactions between the Three Kinds of Structure in Morphology; 7.4 Implications for Language Change; 7.5 Copying: The Operation behind Creative Production; 7.6 Conclusion; 8 The Interplay of Syntagmatic, Schematic, and Paradigmatic Structure; 8.1 Paradigms and Schemas: A Review; 8.2 The Data; 8.3 Naive Discriminative Learner; 8.4 Model 1: Paradigmatic and Schematic Structure; 8.5 Evidence for Copy Outcomes; 8.6 Avoidance vs. Overgeneralization; 8.7 Perseveration; 8.8 The Need for Syntagmatic Structure; 8.9 Model 2: Syntagmatic Structure
520 ▼a A book that uses domain-general learning theory to explain recurrent trajectories of language change. In this book, Vsevolod Kapatsinski argues that language acquisition -- often approached as an isolated domain, subject to its own laws and mechanisms -- is simply learning, subject to the same laws as learning in other domains and well described by associative models. Synthesizing research in domain-general learning theory as it relates to language acquisition, Kapatsinski argues that the way minds change as a result of experience can help explain how languages change over time and can predict the likely directions of language change -- which in turn predicts what kinds of structures we find in the languages of the world. What we know about how we learn (the core question of learning theory) can help us understand why languages are the way they are (the core question of theoretical linguistics). Taking a dynamic, usage-based perspective, Kapatsinski focuses on diachronic universals, recurrent pathways of language change, rather than synchronic universals, properties that all languages share. Topics include associative approaches to learning and the neural implementation of the proposed mechanisms; selective attention; units of language; a comparison of associative and Bayesian approaches to learning; representation in the mind of visual and auditory experience; the production of new words and new forms of words; and automatization of repeated action sequences. This approach brings us closer to understanding why languages are the way they are, Kapatsinski contends, than approaches premised on innate knowledge of language universals and the language acquisition device.
5880 ▼a Print version record.
590 ▼a Added to collection customer.56279.3 - Master record variable field(s) change: 072
650 0 ▼a Language acquisition ▼x Psychological aspects.
650 0 ▼a Linguistic change ▼x Psychological aspects.
650 0 ▼a Psycholinguistics.
650 7 ▼a Language acquisition ▼x Psychological aspects. ▼2 fast ▼0 (OCoLC)fst00992127
650 7 ▼a Psycholinguistics. ▼2 fast ▼0 (OCoLC)fst01081323
650 7 ▼a LANGUAGE ARTS & DISCIPLINES / General ▼2 bisacsh
655 4 ▼a Electronic books.
77608 ▼i Print version: ▼a Kapatsinski, Vsevolod, author. ▼t Changing minds changing tools ▼z 9780262037860 ▼w (DLC) 2017047700 ▼w (OCoLC)1013528123
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