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Authors: Makoto Nakamura 1 ; Yuya Hayashi 2 and Ryuichi Matoba 2

Affiliations: 1 Nagoya University, Japan ; 2 National Institute of Technology, Japan

ISBN: 978-989-758-219-6

Keyword(s): Language Evolution, Simulation, Iterated Learning Model, Cognitive Bias, Statute, Legal Terminology.

Related Ontology Subjects/Areas/Topics: Agent Communication Languages ; Agents ; Artificial Intelligence

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 succ eeded to acquire compositional grammar despite irregular changes in their learning situation. (More)

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Paper citation in several formats:
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

@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},
}

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

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