Modeling the Dynamics of Resource Exchange Networks

Abstract

Understanding the evolution of large-scale cooperation is important for the social welfare and stability of economic and social networks. Therefore, there is a need to model real-world scenarios that involve a trade-off between self-interest and social welfare with minimal artificial assumptions or constraints in a versatile framework. In this paper, we build an agent-based model to simulate the dynamics of a multi-agent, bilateral, resource-exchange network. We analyze how various strategies employed by communities can improve or hurt community payoffs as well as the overall social welfare of the network. We also analyze the role of common knowledge in inducing cooperation in the network. Our experimental evidence from simulations confirms that carefully-designed trading mechanisms can indeed encourage cooperation among communities with various motivations.