M_s_2o_6_k3gn.zip -

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

The .zip file contains the of the algorithms discussed in the paper. The research focuses on: M_S_2o_6_k3gn.zip

: Learning to Control Autonomous Fleets via Sample-Efficient Deep Reinforcement Learning : Optimizing the dispatching and rebalancing of autonomous

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

: 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.