| The Naming game (NG) describes the agreement dynamics of a population of N agents interacting locally in pairs leading to the emergence of a shared vocabulary. This model has its relevance in the novel fields of semiotic dynamics and specifically to opinion formation and language evolution. The application of this model ranges from wireless sensor networks as spreading algorithm, leader election algorithm to user based social tagging systems. In this article, we introduce the concept of overhearing (i.e., at every time step of the game, a random set of N^\delta individuals are chosen from the population that overhears the transmitted word from the speaker and accordingly reshape their inventories). When \delta → 0 we get back the behavior of original NG. As one increases \delta, the population of agents reaches a faster agreement with a significantly low memory requirement. In particular, the convergence time to reach global consensus scales with the population’s size N as 3(1−\delta)/2 log N and simply scales as log N as \delta → 1. |
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