Learnability in Optimality Theory

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Overview

Highlighting the close relationship between linguistic explanation and learnability,Bruce Tesar and Paul Smolensky examine the implications of Optimality Theory (OT) for language learnability. They show how the core principles of OT lead to the learning principle of constraint demotion, the basis for a family of algorithms that infer constraint rankings from linguistic forms.

Of primary concern to the authors are the ambiguity of the data received by the learner and the resulting interdependence of the core grammar and the structural analysis of overt linguistic forms. The authors argue that iterative approaches to interdependencies, inspired by work in statistical learning theory, can be successfully adapted to address the interdependencies of language learning. Both OT and Constraint Demotion play critical roles in their adaptation. The authors support their findings both formally and through simulations. They also illustrate how their approach could be extended to other language learning issues, including subset relations and the learning of phonological underlying forms.

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What People Are Saying

From the Publisher
"This work represents what is arguably the most clear-minded and far-reaching current research program on the applications of formal learning theory to the problem of language acquisition." Stefano Bertolo, Massachusetts Institute of Technology
Stefano Bertolo
This work represents what is arguably the most clear-minded and far-reaching current research program on the applications of formal learning theory to the problem of language acquisition.
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Product Details

  • ISBN-13: 9780262201261
  • Publisher: MIT Press
  • Publication date: 5/8/2000
  • Edition description: New Edition
  • Pages: 148
  • Product dimensions: 6.10 (w) x 9.10 (h) x 0.70 (d)

Meet the Author

Paul Smolensky is Professor of Cognitive Science at Johns Hopkins University. He was a leading member of the PDP connectionist research group, and is the recipient of the 2005 David E. RumelhartPrize in Cognitive Science, which is awarded annually to an individual or collaborative team making a significant contribution to the formal analysis of human cognition.

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Table of Contents

Acknowledgments
1 Language Learning
1.1 What This Books Is About
1.2 Learnability and Universal Grammar
1.3 Decomposing the Learning Problem
1.4 Outline of the Book
2 An Overview of Optimality Theory
2.1 Constraints and Their Violation
2.2 Optimality and Harmonic Ordering
2.3 The Grammar Learning Problem
3 Constraint Demotion
3.1 The Principle of Constraint Demotion
3.2 Analysis of Constraint Demotion
3.3 ErrorDriven Constraint Demotion
4 Overcoming Ambiguity in Overt Forms
4.1 An Optimality Theoretic System of Stress Grammars
4.2 Robust Interpretive Parsing
4.3 The RIP/CD Learning Procedure
4.4 Getting Stuck: How RIP/CD Can Fail
4.5 Simulation Results: Metrical Stress
4.6 Discussion
5 Issues in Language Learning
5.1 The Subset Principle, Richness of the Base, and Acquisition
Theory
5.2 Learning Underlying Forms
6 Learnability and Linguistic Theory
6.1 Parametric Independence and Linguistic Explanation
6.2 Summary
7 Correctness and Data Complexity of Constraint
Demotion
7.1 Stratified Hierarchies
7.2 The Target Stratified Hierarchy
7.3 Constraint Demotion
7.4 Extension to Arbitrary Initial Hierarchies
7.5 ErrorDriven Constraint Demotion
7.6 Recursive Constraint Demotion
8 ProductionDirected Parsing
8.1 The Parsing Problem in Optimality Theory
8.2 Formalizing CVT
8.3 Parsing with CVT
8.4 A Sample Parse
8.5 Interpretive Parsing
8.6 Discussion
8.7 The Rest of the Operations Set
Notes
References
Index
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