Self-organization of vocabularies under different interaction orders

TL;DR

This paper investigates how the order of interactions among agents influences the formation of vocabularies, using Automata Networks to model and simulate the process on two-dimensional lattices.

Contribution

It introduces a novel approach to study the impact of interaction order on vocabulary formation using Automata Networks, extending beyond traditional random pair negotiations.

Findings

Vocabulary formation features are similar under random and structured interaction schemes.

Automata Networks effectively model the influence of interaction order.

Simulations show robustness of word-meaning association formation across different update schemes.

Abstract

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.