Fuzzy referral based cooperation in social networks of agents
Since intelligent agents aim to represent human reasoning and behaviour, multiagent systems are supposed to reflect the collective behaviour of human societies. In human societies, each individual determine who collaborate with, and this selected group forms a social network that will improve the quality of the decisions of individuals. Several models of computation have been proposed in literature. Among them, the approach of the authors relies on the ability of fuzzy logic to operate with vague and uncertain terms. This paper studies how much effective is the cooperation between agents modelled by these proposals in different scenarios. The scenarios test the evolution of the deception caused by overvalued/undervalued predictions, with cooperation of low/high reliability, and with three different levels of variability in the behaviour of the agents evaluated.
social networks fuzzy logic cooperative agents