M_s_2o_6_k3gn.zip -

: The authors introduce a decentralized training method with centralized execution that handles the large, dynamic scale of urban transport networks.

: Optimizing the dispatching and rebalancing of autonomous vehicle fleets (e.g., ride-sharing services) to minimize wait times and maximize efficiency. M_S_2o_6_k3gn.zip

: Learning to Control Autonomous Fleets via Sample-Efficient Deep Reinforcement Learning : The authors introduce a decentralized training method

: Filippos Christianos, Georgios Papoudakis, Aris Filos, and Stefano V. Albrecht. M_S_2o_6_k3gn.zip

The .zip file contains the of the algorithms discussed in the paper. The research focuses on:

: Originally published in Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021) . Context of the File