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April 2006
7 x 9, 502 pp., 54 illus.
$42.00/£31.95 (CLOTH)
Short

ISBN-10:
0-262-14094-2
ISBN-13:
978-0-262-14094-2

Other Editions
Paper (2009)
Series
Current Studies in Linguistics
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The Computational Nature of Language Learning and Evolution
Partha Niyogi

Preface
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xiii
Acknowledgmentsxvii
IThe Problem1
1Introduction
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3
    1.1Language Acquisition8
    1.2Variation -- Synchonic and Diachronic13
    1.3More Examples of Change16
    1.4Perspective and Conceptual Issues25
    1.5Evolution in Linguistics and Biology32
    1.6Summary of Results37
    1.7Audience and Connections to Other Fields42
IILanguage Learning47
2Language Acquisition: The Problem of Inductive Inference49
    2.1A Framework for Learning50
    2.2The Inductive Inference Approach56
    2.3The Probably Approximately CorrectModel and the VC Theorem71
3Language Acquisition: A Linguistic Treatment83
    3.1Language Learning and the Poverty of Stimulus86
    3.2Constrained Grammars — Principles and Parameters88
    3.3Learning in the Principles and Parameters Framework96
    3.4Formal Analysis of the Triggering Learning Algorithm100
    3.5Conclusions111
    3.6Appendix113
4Language Acquisition: Memoryless Learning117
    4.1Characterizing Convergence Times for the Markov Chain Model117
    4.2Exploring Other Points129
    4.3Batch Learning Upper and Lower Bounds: An Aside135
    4.4Generalizations and Variations138
    4.5Other Kinds of Learning Algorithms142
    4.6Conclusions144
    4.7Appendix: Proofs for Memoryless Algorithms146
IIILanguage Change153
5Language Change: A Preliminary Model155
    5.1An Acquisition-Based Model of Language Change157
    5.2A Preliminary Model160
    5.3Implications and Further Directions177
6Language Change: Multiple Languages187
    6.1Multiple Languages187
    6.2Example 1: A Three-Parameter System195
    6.3Example 2: Syntactic Change in French218
    6.4Conclusions229
7An Application to Portuguese233
    7.1Portuguese: A Case Study234
    7.2The Logical Basis of Language Change238
    7.3Conclusions248
8An Application to Chinese Phonology251
    8.1Phonological Merger in the Wenzhou Province252
    8.2Two Forms in a Population257
    8.3Examining the Wenzhou Data Further265
    8.4Error-Driven Models268
    8.5Discussion271
    8.6Conclusions273
9A Model of Cultural Evolution and Its Application to Language275
    9.1Background275
    9.2The Cavalli-Sforza and Feldman Theory277
    9.3Instantiating the CF Model for Languages279
    9.4CF Models for Some Simple Learning Algorithms284
    9.5A Generalized NB Model for Neighborhood Effects298
    9.6A Note on Oblique Transmission302
    9.7Conclusions303
10Variations and Case Studies305
    10.1Finite Populations305
    10.2Spatial Effects314
    10.3Multilingual Learners320
    10.4Conclusions336
IVThe Origin of Language339
11The Origin of Communicative Systems: Communicative Efficiency341
    11.1Communicative Efficiency of Language343
    11.2Communicability for Linguistic Systems346
    11.3Reaching the Highest Communicability351
    11.4Implications for Learning359
    11.5Communicative Efficiency and Linguistic Structure366
12The Origin of Communicative Systems: Linguistic Coherence and Communicative Fitness375
    12.1General Model376
    12.2Dynamics of a Fully Symmetric System379
    12.3Fidelity of Learning Algorithms392
    12.4Asymmetric A Matrices398
    12.5Conclusions402
13The Origin of Communicative Systems: Linguistic Coherence and Social Learning405
    13.1Learning Only from Parents406
    13.2Social Learning: Learning from Everybody408
    13.3Coherence for General n415
    13.4Proofs of Evolutionary Dynamics Results418
    13.5Coherence for a Memoryless Learner432
    13.6Learning in Connected Societies433
    13.7Conclusions441
VConclusions443
14Conclusions
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445
    14.1A Summary of the Major Insights446
    14.2Future Directions449
    14.3A Concluding Thought458
Bibliography
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459
Index
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479
 
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