Population Dynamics of Grammar Acquisition

  • Natalia L. Komarova
  • Martin A. Nowak

Abstract

The most fascinating aspect of human language is grammar. Grammar is a computational system that mediates a mapping between linguistic form and meaning. Grammar is the machinery that gives rise to the unlimited expressibility of human language.

Keywords

Coherence Weinstein 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bates E (1984) Bioprograms and the innateness hypothesis. Behavioral and Brain Sciences, 7: 188–190CrossRefGoogle Scholar
  2. Cangelosi A, Parisi D (1998) The emergence of a ‘language’ in an evolving population of neural networks. Connection Science, 10: 83–97CrossRefGoogle Scholar
  3. Cangelosi A (1999) Modeling the evolution of communication: From stimulus associations to grounded symbolic associations. In: Floreano D, Nicoud JD, Mondada F (eds) Proceedings of ECAL99 the Fifth European Conference on Artificial Life (Lecture Notes in Artificial Intelligence). Springer-Verlag, BerlinGoogle Scholar
  4. Chomsky N (1965) Aspects of the theory of syntax. MIT Press, Cambridge MAGoogle Scholar
  5. Chomsky N (1972) Language and mind. Harcourt Brace Jovanovich, New YorkGoogle Scholar
  6. Eigen M, Schuster P (1979) The Hypercycle: A principle of natural self-organisation. Springer, BerlinGoogle Scholar
  7. Gibson E, Wexler K (1994) Triggers. Linguistic Inquiry, 25: 407–454Google Scholar
  8. Gold EM (1967) Language identification in the limit. Information and Control, 10: 447–474MATHCrossRefGoogle Scholar
  9. Hashimoto T, Ikegami T (1996) Emergence of net-grammar in communicating agents. BioSystems, 38: 1–14CrossRefGoogle Scholar
  10. Hofbauer J, Sigmund K (1998) Evolutionary games and replicator dynamics. Cambridge University PressGoogle Scholar
  11. Hornstein NR, Lightfoot DW (1981) Explanation in linguistics. Longman, LondonGoogle Scholar
  12. Hurford J, Studdert-Kennedy M, Knight C (eds) (1998) Approaches to the evolution of language. Cambridge University Press, Cambridge UKGoogle Scholar
  13. Jackendoff R (1997) The architecture of the language faculty. MIT Press, Cambridge MAGoogle Scholar
  14. Kirby S (1999) Syntax out of learning: The cultural evolution of structured communication in a population of induction algorithms In: Floreano D, Nicoud JD, Mondada F (eds) Proceedings of ECAL99 the Fifth European Conference on Artificial Life (Lecture Notes in Artificial Intelligence). Springer-Verlag, Berlin, pp 694–703Google Scholar
  15. Komarova NL (2001) Population dynamics of language learning. Manuscript in preparationGoogle Scholar
  16. Komarova NL, Niyogi P, Nowak MA (2001) Evolutionary dynamics of grammar acquisition. Journal of Theoretical Biology, 209(1): 43–59CrossRefGoogle Scholar
  17. Komarova NL, Niyogi P (2001) Optimizing the mutual intelligibility of linguistic agents in a shared world. To be submitted to Artificial Intelligence Google Scholar
  18. Komarova NL, Nowak MA (2001) Natural selection of the critical period for grammar acquisition, Proceedings of the Royal Society B, 268(1472): 1189–1196CrossRefGoogle Scholar
  19. Komarova NL, Rivin I (2001a) Harmonic mean, random polynomials and stochastic matrices. Submitted to Advances in Applied Mathematics. (arXiv.org preprint mathPR/0105236)Google Scholar
  20. Komarova NL, Rivin I (2001b) Mathematics of learning, Submitted to Electr Ann of the AMS (arXiv.org preprint math PR/0105235)Google Scholar
  21. Langacker, R (1987) Foundations of cognitive grammar (Volume 1). Stanford University Press, Stanford CAGoogle Scholar
  22. Langacker R (1992) Foundations of cognitive grammar (Volume 2). Stanford University Press, Stanford CAGoogle Scholar
  23. Lightfoot D (1991) How to set parameters: Arguments from language change. MIT Press, Cambridge MAGoogle Scholar
  24. Manzini R, Wexler K (1987) Parameters, Binding Theory, and learnability. Linguistic Inquiry, 18: 413–444Google Scholar
  25. Niyogi P, Berwick RC (1996) A language learning model for finite parameter spaces. Cognition, 61: 161–193CrossRefGoogle Scholar
  26. Niyogi P, Berwick RC (1997) Evolutionary consequences of language learning. Linguistics and Philosophy, 20: 697–719CrossRefGoogle Scholar
  27. Niyogi P (1998) The informational complexity of learning. Kluwer Academic Publishers, BostonMATHCrossRefGoogle Scholar
  28. Noble J (1999) Cooperation, conflict and the evolution of communication. Adaptive Behavior, 7(3/4): 349–370CrossRefGoogle Scholar
  29. Nowak MA, Komarova NL, Niyogi P (2001) Evolution of universal grammar. Science, 291: 114–118MathSciNetCrossRefGoogle Scholar
  30. Osherson D, Stob M, Weinstein S (1986) Systems that learn. MIT Press, Cambridge MAGoogle Scholar
  31. Rivin I (2001) UnpublishedGoogle Scholar
  32. Steels L (1997) The synthetic modelling of language origins, Evolution of Communication 1: 1–34CrossRefGoogle Scholar
  33. Tomasello M (1995) Language is not an instinct. Cognitive Development, 10: 131–156CrossRefGoogle Scholar
  34. Valiant LG (1984) A theory of the learnable. Communications of the ACM, 27: 436–445CrossRefGoogle Scholar
  35. Vapnik V (1995) The nature of statistical learning theory. Springer, New YorkMATHGoogle Scholar
  36. Wexler K, Culicover P (1980) Formal principles of language acquisition. MIT Press, Cambridge MAGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2002

Authors and Affiliations

  • Natalia L. Komarova
  • Martin A. Nowak

There are no affiliations available

Personalised recommendations