Simulation of Language Evolution based on Actual Diachronic Change Extracted from Legal Terminology

Makoto Nakamura, Yuya Hayashi, Ryuichi Matoba

Abstract

Simulation studies have played an important role in language evolution. Although a variety of methodologies have been proposed so far, they are typically too abstract to recognize that their learning mechanisms properly reflect actual ones. One reason comes from the lack of empirical data recorded for a long period with explicit description. Our purpose in this paper is to show simulation models adapt to actual language change. As empirical diachronic data, we focus on a statutory corpus. In general, statutes define important legal terms with explanatory sentences, which are also revised by amendment. We proposed an iterated learning model, in which an infant agent learns grammar through his/her parent’s utterances about legal terms and their semantic relations, and the infant becomes a parent in the next generation. The key issue is that the learning situation about legal terms and their relations can be changed due to amendment. Our experimental result showed that infant agents succeeded to acquire compositional grammar despite irregular changes in their learning situation.

References

  1. Bickerton, D. (1990). Language and Species. University of Chicago Press.
  2. Briscoe, E. J., editor (2002). Linguistic Evolution through Language Acquisition: Formal and Computational Models. Cambridge University Press.
  3. Cangelosi, A. and Parisi, D., editors (2002). Simulating the Evolution of Language. Springer, London.
  4. Chomsky, N. (1980). Rules and Representations. Basil Blackwell, Oxford.
  5. Chomsky, N. (1986). Knowledge of Language:Its Nature, Origin, and Use. Praeger, New York.
  6. Hansen, M. B. and Markman, E. M. (2009). Children's use of mutual exclusivity to learn labels for parts of objects. Developmental Psychology, 45(2):592-596.
  7. Hurford, J. R. (2002). The Roles of Expression and Representation in Language Evolution. In The Transition to Language, pages 311-334. Oxford University Press, Cambridge.
  8. Imai, M. and Gentner, D. (1997). A cross-linguistic study of early word meaning: Universal ontology and linguistic influence. Cognition, 62(2):169-200.
  9. Kirby, S. (2002). Learning, bottlenecks and the evolution of recursive syntax. In Briscoe, T., editor, Linguistic Evolution through Language Acquisition: Formal and Computational Models, chapter 6. Cambridge University Press.
  10. Lyon, C., Nehaniv, C., and Cangelosi, A., editors (2007). Emergence of Communication and Language. Springer.
  11. Markman, E. M. (1990). Constraints children place on word meanings. Cognitive Science, 14(1):57-77.
  12. Matoba, R., Nakamura, M., and Tojo, S. (2010). Efficiency of the symmetry bias in grammar acquisition. Information and Computation, 209(3):536-547.
  13. Nakamura, M., Matoba, R., and Tojo, S. (2015). Simulation of Emergence of Local Common Languages Using Iterated Learning Model on Social Networks. International Journal on Advances in Intelligent Systems, 8(3&4):374-384.
  14. Nakamura, M., Ogawa, Y., and Toyama, K. (2016). Development of Diachronic Terminology from Japanese Statutory Corpora. Journal of Open Access to Law, 4(1):16 pages.
  15. Quine, W. V. O. (1960). Word and Object. MIT Press.
  16. Sudo, H., Matoba, R., Cooper, T., and Tsukada, A. (2016). Effect of the Symmetry Bias on Linguistic Evolution. Artificial Life and Robotics, 21(2):207-214.
  17. Sudo, H., Matoba, R., Hagiwara, S., Nakamura, M., and Tojo, S. (2013). Knowledge Revision based on Efficacy of Cognitive Biases in First Language Acquisition. In Proceedings of the 30th Annual Meeting of the Japanese Cognitive Science Society, pages 343-349.
  18. Wilke, A. and Mata, R. (2012). Cognitive Bias. Encyclopedia of Human Behaviour, 1:531-535.
  19. Winkels, R. and Hoekstra, R. (2012). Automatic Extraction of Legal Concepts and Definitions. In Legal Knowledge and Information Systems - JURIX 2012: The Twenty-Fifth Annual Conference, pages 157-166.
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Paper Citation


in Harvard Style

Nakamura M., Hayashi Y. and Matoba R. (2017). Simulation of Language Evolution based on Actual Diachronic Change Extracted from Legal Terminology . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 343-350. DOI: 10.5220/0006291903430350


in Bibtex Style

@conference{icaart17,
author={Makoto Nakamura and Yuya Hayashi and Ryuichi Matoba},
title={Simulation of Language Evolution based on Actual Diachronic Change Extracted from Legal Terminology},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={343-350},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006291903430350},
isbn={978-989-758-219-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Simulation of Language Evolution based on Actual Diachronic Change Extracted from Legal Terminology
SN - 978-989-758-219-6
AU - Nakamura M.
AU - Hayashi Y.
AU - Matoba R.
PY - 2017
SP - 343
EP - 350
DO - 10.5220/0006291903430350