Manipulating convention emergence using influencer agents

Coordination in open multi-agent systems (MAS) can reduce costs to agents associated with conflicting goals and actions, allowing artificial societies to attain higher levels of aggregate utility. Techniques for increasing coordination typically involve incorporating notions of conventions, namely socially adopted standards of behaviour, at either an agent or system level. As system designers cannot necessarily create high quality conventions a priori, we require an understanding of how agents can dynamically generate, adopt and adapt conventions during their normal interaction processes. Many open MAS domains, such as peer-to-peer and mobile ad-hoc networks, exhibit properties that restrict the application of the mechanisms that are often used, especially those requiring the incorporation of additional components at an agent or society level. In this paper, we use Influencer Agents (IAs) to manipulate convention emergence, which we define as agents with strategies and goals chosen to aid the emergence of high quality conventions in domains characterised by heterogeneous ownership and uniform levels of agent authority. Using the language coordination problem (Steels in Artif Life 2(3):319-392, 1995), we evaluate the effect of IAs on convention emergence in a population. We show that relatively low proportions of IAs can (i) effectively manipulate the emergence of high-quality conventions, and (ii) increase convention adoption and quality. We make no assumptions involving agent mechanism design or internal architecture beyond the usual assumption of rationality. Our results demonstrate the fragility of convention emergence in the presence of malicious or faulty agents that attempt to propagate low quality conventions, and confirm the importance of social network structure in convention adoption.