Mean Field Equilibria for Resource Competition in Spatial Settings

Abstract

We study a model of competition among nomadic agents for time-varying and location-specific resources arising in crowdsourced transportation services, online communities, and traditional location-based economic activity. This model comprises a group of agents and a single location endowed with a dynamic stochastic resource process. Periodically, each agent derives a reward determined by the location’s resource level and the number of other agents there and has to decide whether to stay at the location or move. On moving, the agent arrives at a different location whose dynamics are independent of and identical to the original location. Using the methodology of mean field equilibrium, we study the equilibrium behavior of the agents as a function of the dynamics of the stochastic resource process and the nature of the competition among colocated agents. We show that an equilibrium exists in which each agent decides whether to switch locations based only on the agent’s current location’s resource level and the number of other agents there. We additionally show that when an agent’s payoff is decreasing in the number of other agents at the agent’s location, equilibrium strategies obey a simple threshold structure. We show how to exploit this structure to compute equilibria numerically and use these numerical techniques to study how system structure affects the agents’ collective ability to explore their domain to find and effectively utilize resource-rich areas.