Fast Convention Formation in Dynamic Networks Using Topological Knowledge

Abstract

In this paper, we design a distributed mechanism that is able to create a social convention within a large convention space for multiagent systems (MAS) operating on various topologies. Specifically, we investigate a language coordination problem in which agents in a dynamic MAS construct a common lexicon in a decentralized fashion. Agent interactions are modeled using a language game where every agent repeatedly plays with its neighbors. Each agent stochastically updates its lexicons based on the utility values of the received lexicons from its immediate neighbors. We present a novel topology-aware utility computation mechanism and equip the agents with the ability to reorganize their neighborhood based on this utility estimate to expedite the convention formation process. Extensive simulation results indicate that our proposed mechanism is both effective (able to converge into a large majority convention state with more than 90\% agents sharing a high-quality lexicon) and efficient (faster) as compared to state-of-the-art approaches for social conventions in large convention spaces.