Analogical Modeling (AM) is an exemplar-based general theory of description that uses both neighbors and non-neighbors (under certain well-defined conditions of homogeneity) to predict language behavior. This book provides a basic introduction to AM, compares the theory with nearest-neighbor approaches, and discusses the most recent advances in the theory, including psycholinguistic evidence, applications to specific languages, the problem of categorization, and how AM relates to alternative approaches of language description (such as instance families, neural nets, connectionism, and optimality theory). The book closes with a thorough examination of the problem of the exponential explosion, an inherent difficulty in AM (and in fact all theories of language description). Quantum computing (based on quantum mechanics with its inherent simultaneity and reversibility) provides a precise and natural solution to the exponential explosion in AM. Finally, an extensive appendix provides three tutorials for running the AM computer program (available online).
1. List of contributors; 2. Introduction (by Skousen, Royal); 3. Part I. The basics of Analogical Modeling; 4. 1. An overview of Analogical Modeling (by Skousen, Royal); 5. 2. Issues in Analogical Modeling (by Skousen, Royal); 6. Part II. Psycholinguistic evidence for Analogical Modeling; 7. 3. Skousen's analogical approach as an exemplar-based model of categorization (by Chandler, Steve); 8. Part III. Applications to specific languages; 9. 4. Applying Analogical Modeling to the German plural (by Wulf, Douglas J.); 10. 5. Testing Analogical Modeling: The /k/~O alternation in Turkish (by Rytting, C. Anton); 11. Part IV. Comparing Analogical Modeling with TiMBL; 12. 6. A comparison of two analogical models: Tilburg Memory-Based Learner versus Analogical Modeling (by Eddington, David); 13. 7. A comparison of Analogical Modeling to Memory-Based Language Processing (by Daelemans, Walter); 14. 8. Analogical hierarchy: Exemplar-based modeling of linkers in Dutch noun-noun compounds (by Krott, Andrea); 15. Part V. Extending Analogical Modeling; 16. 9. Expanding k -NN analogy with instance families (by Bosch, Antal van den); 17. 10. Version spaces, neural networks, and Analogical Modeling (by Mudrow, Mike); 18. 11. Exemplar-driven analogy in Optimality Theory (by Myers, James); 19. 12. The hope for analogous categories (by Johansson, Christer); 20. Part VI. Quantum computing and the exponential explosion; 21. 13. Analogical Modeling and quantum computing (by Skousen, Royal); 22. Part VII. Appendix; 23. 14. Data files for Analogical Modeling (by Lonsdale, Deryle); 24. 15. Running the Perl/C version of the Analogical Modeling program (by Parkinson, Dilworth B.); 25. 16. Implementing the Analogical Modeling algorithm (by Stanford, Theron); 26. Index
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