The Design of Desired Collectives with Agent-based Simulation

In this paper, I consider the issue of efficient and equitable utilization of limited resources by a collection of interacting agents. There is no presumption that a collective decision of interacting agents leads to a collectively satisfactory result without any central authority. How well agents do for it in adapting to their environment is not the same thing as how satisfactory an environment they collectively create. Agents normally react to others’ decisions, and the resulting volatile collective decision is often far from being efficient. By means of agent -based simulation, I explore a new approach for designing desirable collectives. There are two closely related issues concerning collectives, the forward problem and the inverse problem. The forward problem is to investigate what a collective of interacting agents determines its complex emergent behavior. The inverse problem is to investigate how each agent learns to behave for a desirable collective. I discuss how agent-based simulation contributes to solve these two issues.