Multiagent Reinforcement Learning for Autonomous Routing and Pickup Problem with Adaptation to Variable Demand
Daniel Garces,Sushmita Bhattacharya,Stephanie Gil,Dimitri Bertsekas,Daniel Garces,Sushmita Bhattacharya,Stephanie Gil,Dimitri Bertsekas
We derive a learning framework to generate routing/pickup policies for a fleet of autonomous vehicles tasked with servicing stochastically appearing requests on a city map. We focus on policies that 1) give rise to coordination amongst the vehicles, thereby reducing wait times for servicing requests, 2) are non-myopic, and consider a-priori potential future requests, 3) can adapt to changes in the...
