Terms of Use: 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.
: Learning to Control Autonomous Fleets via Sample-Efficient Deep Reinforcement Learning
: The authors introduce a decentralized training method with centralized execution that handles the large, dynamic scale of urban transport networks.
: 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.
: Learning to Control Autonomous Fleets via Sample-Efficient Deep Reinforcement Learning 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. : A novel Deep Reinforcement Learning (DRL) approach
