A Modular and Transferable Reinforcement Learning Framework for the Fleet Rebalancing Problem

no code implementations • 27 May 2021 • Erotokritos Skordilis, Yi Hou, Charles Tripp, Matthew Moniot, Peter Graf, David Biagioni

To help bridge the gap between novel and existing methods, we propose a modular framework for fleet rebalancing based on model-free reinforcement learning (RL) that can leverage an existing dispatch method to minimize system cost.

Decision Making reinforcement-learning +2