Valuation of Cooperation and Defection in Small-World Networks : A Behavioral Robotic Approach

Valuation of behaviors in a social network is a very complex task due to dynamic nature of interactions, changes in behaviors and difficulties in defining the norms to evaluate the behaviors. Though, this valuation is a mandatory first step in studying evolution of behaviors in social networks. Therefore, in this paper two major game theoretical behaviors in social networks, namely Cooperation and Defection are programmed in members of a large group of robots. Various experiments on the multi-robot system are carried out to study the fitness of individuals who have adopted each of these behaviors in a Small-Worldlike environment compared to a Regular environment. The results of this study reveal one of the important characteristics of small-world networks in which individuals are not directly connected to one another, but have indirect links to every other via a small number of intermediate individuals: The more individuals adopt Cooperation in a small-world environment the less benefits they’ll get in the group. In contrast, our results show that in regular environments where no short connection exists between most of the individuals, a reverse phenomenon is seen: The cooperators surpass defectors once they are in the majority. Such kind of results suggest that, by getting advantage of the proposed multi-robot framework, valuable contributions can be delivered to the field of social science.