AAAI 2023technical3 citations
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.
BibTeX
@article{Cipolina-Kun_2024, title={Enhancing Smart, Sustainable Mobility with Game Theory and Multi-Agent Reinforcement Learning With Applications to Ridesharing}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/26917}, DOI={10.1609/aaai.v37i13.26917}, abstractNote={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.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Cipolina-Kun, Lucia}, year={2024}, month={Jul.}, pages={16113-16114} }