Enhancing Smart, Sustainable Mobility with Game Theory and Multi-Agent Reinforcement Learning With Applications to Ridesharing

Abstract

We propose the use of game-theoretic solutions and multi- agent Reinforcement Learning in the mechanism design of smart, sustainable mobility services. In particular, we present applications to ridesharing as an example of a cost game.