Potential Games Design Using Local Information
This work addresses the challenge of aligning individual player incentives with a global objective under information constraints, relevant for distributed multiagent systems.
The paper proposes a method to design potential games using only local information, ensuring the system-level objective function serves as the potential function. The approach is validated through a consensus problem in multiagent systems.
Consider a multiplayer game, and assume a system level objective function, which the system wants to optimize, is given. This paper aims at accomplishing this goal via potential game theory when players can only get part of other players' information. The technique is designing a set of local information based utility functions, which guarantee that the designed game is potential, with the system level objective function its potential function. First, the existence of local information based utility functions can be verified by checking whether the corresponding linear equations have a solution. Then an algorithm is proposed to calculate the local information based utility functions when the utility design equations have solutions. Finally, consensus problem of multiagent system is considered to demonstrate the effectiveness of the proposed design procedure.