Scalability of evolving networks of trading agents

Scalability is a vital issue for multi-agent systems. In this paper, we present a trading model of a real-world scenario. It is modelled as networks of interacting agents that can evolve automatically over time, based on behaviors of agents and system configurations. In this model, the agents have resources, and receive a payoff for selling the resources. Agents are regarded as players in a game. We describe an artigicial multi-agent ecosystem where the Darwin's theory of natural selection were applied. as evolutionary dynamics on the population of agents. Through discrete event simulations, the scalability of this model under various system configurations is analyzed and scaling laws are derived.