Agent-Network-Computation-Based Evolutionary Game Model in Language Competition

As language is intrinsic to the expression of culture, the rise and fall of a language directly affect the culture associated with it. Therefore, constructing a computational model to study the mechanisms of language competition and explore policies of language preservation is very important. We address the language system’s macroscopic aspects, such as the prestige of languages, the difficulty level of learning languages, and natives’ tolerance toward nonnative languages, as well as individual interactions at the microscopic level, and then propose an agent network computation-based evolutionary game model (ANC-EGM), including two major components—the definition of language attractiveness and the language competition game, to model a more realistic dynamic evolving language system. The replicator equation is adopted to solve the evolutionary equilibrium, and the stability of the equilibrium points is analyzed by the local stability analysis of the Jacobian matrix. The theoretical analysis and simulations illustrate that the ANC-EGM can comprehensively model the competition between two languages and estimate how individual interactions lead to the demise or coexistence of languages. We further validate the conclusions of the ANC-EGM on the empirical data of the Minnan dialect and Mandarin, which show that the ANC-EGM can provide an experimental computing platform for the in-depth study of language policy regulation and language evolution rules.