Steering the distribution of agents in mean-field and cooperative games
The paper provides a theoretical foundation for controlling agent distributions in mean-field and cooperative games, which is relevant for multi-agent systems and swarm robotics.
This work addresses the problem of steering a collection of weakly interacting agents to a specified terminal distribution. The authors prove that the map between terminal costs and terminal probability distributions is onto, extending optimal mass transport theory.
The purpose of this work is to pose and solve the problem to guide a collection of weakly interacting dynamical systems (agents, particles, etc.) to a specified terminal distribution. The framework is that of mean-field and of cooperative games. A terminal cost is used to accomplish the task; we establish that the map between terminal costs and terminal probability distributions is onto. Our approach relies on and extends the theory of optimal mass transport and its generalizations.