Approximate Multiagent Reinforcement Learning for On-Demand Urban Mobility Problem on a Large Map
Daniel Garces,Sushmita Bhattacharya,Dimitri Bertsekas,Stephanie Gil,Daniel Garces,Sushmita Bhattacharya,Dimitri Bertsekas,Stephanie Gil
In this paper, we focus on the autonomous multiagent taxi routing problem for a large urban environment where the location and number of future ride requests are unknown a-priori, but can be estimated by an empirical distribution. Recent theory has shown that a rollout algorithm with a stable base policy produces a near-optimal stable policy. In the routing setting, a policy is stable if its execu...
