The Computational Nature of Language Learning and Evolution 1st Edition by Partha Niyogi, Samuel Jay Keyser ISBN 026228068X 9780262280686

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ISBN 10: 026228068X 
ISBN 13: 9780262280686
Author: Partha Niyogi, Samuel Jay Keyser

The Computational Nature of Language Learning and Evolution by Partha Niyogi, published by MIT Press in 2006, offers a comprehensive framework for understanding the interplay between language acquisition and linguistic evolution through a computational lens. Niyogi, a professor of Computer Science and Statistics at the University of Chicago, integrates formal language theory, learning theory, and evolutionary dynamics to model how language is learned by individuals and how it evolves over generations. He presents a mathematical and computational approach to analyze the subtle relationships between individual learning processes and population-level language changes, drawing parallels to Darwinian evolution. The book delves into topics such as the role of universal grammar, the dynamics of language change, and the cultural evolution of language, providing insights into the mechanisms that drive the emergence and transformation of linguistic systems over time.

The Computational Nature of Language Learning and Evolution 1st Table of contents:

Part I: Foundations of Language and Computation

1. The Nature of Language

   • Defining Language

   • Structure and Universals

2. Computational Approaches to Language

   • Symbolic vs. Statistical Models

   • Neural and Connectionist Frameworks

3. Cognitive Constraints on Language Learning

   • Memory, Attention, and Processing

   • Innateness and Experience

Part II: Language Acquisition
4. Learning Mechanisms in Humans

• Phonology and Morphology

• Syntax and Semantics

5. Computational Models of Language Learning

   • Bayesian Inference

   • Neural Network Models

   • Reinforcement Learning Approaches

6. Multilingual and Cross-Cultural Learning

   • Transfer Effects

   • Emergent Patterns Across Languages

Part III: Language Evolution
7. Evolutionary Perspectives

• Biological Evolution of Language

• Cultural Evolution and Transmission

8. Modeling Language Change

   • Agent-Based Models

   • Network Models and Simulation

9. Emergence of Complexity

   • From Simple Signals to Grammar

   • Iterated Learning and Optimization

Part IV: Integrative Perspectives
10. Computational and Cognitive Synthesis
– Bridging Learning and Evolution
– Predictive Models of Language Dynamics
11. Future Directions
– AI and Language Simulation
– Open Questions in Language Evolution Research

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Tags: Partha Niyogi, Samuel Jay Keyser, Computational Nature, Language Learning