Enabling imitation-based cooperation in dynamic social networks

The emergence of cooperation among self-interested agents has been a key concern of the multi-agent systems community for decades. With the increased importance of network-mediated interaction, researchers have shifted the attention to the impact of social networks and their dynamics in promoting or hindering cooperation, drawing various context-dependent conclusions. For example, some lines of research, theoretical and experimental, suggest the existence of a threshold effect in the ratio of timescales of network evolution, after which cooperation will emerge, whereas other lines dispute this, suggesting instead a Goldilocks zone. In this paper we provide an evolutionary game theory framework to understand coevolutionary processes from a bottom up perspective - in particular the emergence of a cooperator-core and defector-periphery - clarifying the impact of partner selection and imitation strategies in promoting cooperative behaviour, without assuming underlying communication or reputation mechanisms. In doing so we provide a unifying framework to study imitation-based cooperation in dynamic social networks and show that disputes in the literature can in fact coexist in so far as the results stem from different equally valid assumptions.

Automated summary

The emergence of cooperation among self-interested agents has long been a concern for the multi-agent systems community. With the rise of social networks, researchers have started focusing on the impact of social networks and their dynamics on cooperation, leading to different conclusions. This paper presents an evolutionary game theory framework to understand the emergence of cooperation from a bottom-up perspective, clarifying the role of partner selection and imitation strategies in promoting cooperative behavior.