2025 NAACL NAACL 2025

Creolization versus code-switching: An agent-based cognitive model for bilingual strategies in language contact

Abstract

AbstractCreolization and code-switching are closely related contact-induced linguistic phenomena, yet little attention has been paid to the connection between them. In this paper, we propose an agent-based cognitive model which provides a linkage between these two phenomena focusing on the statistical regularization of language use. That is, we identify that creolization as a conventionalization process and code-switching as flexible language choice can emerge from the same cognitive model in different social environments. Our model postulates a social structure of bilingual and monolingual populations, in which a set of agents seek for optimal communicative strategy shaped by multiple cognitive constraints. The simulation results show that our model successfully captures both phenomena as two ends of a continuum, characterized by varying degrees of regularization in the use of linguistic constructions from multiple source languages. The model also reveals a subtle dynamic between social structure and individual-level cognitive constraints.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary and Machine Learning
🧭 Keyword Pioneer — agent-based cognitive model
🐝 Cross-Pollinator — Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio