Simulation of language competition by bilingual agents

Rakesh Kumar and ShivKishan Dubey

International Journal of Knowledge and Learning, 2018, vol. 12, issue 4, 362-378

Abstract: In the language transmission, a person shares different ways of own lexicons to others and each one is able to reproduce new lexicons through the old ones. Our objective is to explore how lexicons can be modified in synchronic or diachronic scenarios during the interaction of two different languages (L1 or L2) community agents. In this research, a new model has been proposed within language competition game strategy using bilingual agents. The outcome of shared lexicons in the synchronic scenario is that massive codes of second-language are affected and propagated into future generation successfully. Initially, we take matured agents who are stimulated by iterated learning model (ILM) and equipped with own grammar rules. Using Levenshtein Distance, these agents modify own old lexicons and generate new ones for the next generation. This game strategy is restricted to synchronic only and found that second language always wins this game.

Keywords: NLP; natural language processing; iterated learning model; language acquisition; bilingualism; exposure ratio. (search for similar items in EconPapers)
Date: 2018
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