Self-organization of vocabularies under different interaction orders
This work addresses a novel aspect of language evolution modeling, but it is incremental as it builds on existing frameworks like the Naming Game.
The paper investigates how the order of interactions affects vocabulary formation in agent-based models, finding that random updates of small population fractions on 2D lattices reproduce typical word-meaning association features.
Traditionally, the formation of vocabularies has been studied by agent-based models (specially, the Naming Game) in which random pairs of agents negotiate word-meaning associations at each discrete time step. This paper proposes a first approximation to a novel question: To what extent the negotiation of word-meaning associations is influenced by the order in which the individuals interact? Automata Networks provide the adequate mathematical framework to explore this question. Computer simulations suggest that on two-dimensional lattices the typical features of the formation of word-meaning associations are recovered under random schemes that update small fractions of the population at the same time.