: Originally published in Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021) . Context of the File
: A novel Deep Reinforcement Learning (DRL) approach that uses a hierarchical structure to improve "sample efficiency," meaning the system learns effective strategies using significantly less data than traditional methods. M_S_2o_6_k3gn.zip
: Learning to Control Autonomous Fleets via Sample-Efficient Deep Reinforcement Learning : Originally published in Proceedings of the 20th