2 citations · 3 across the 3 of their papers we have counts for
3 papers
Multi-Agent Soft Actor-Critic with Coordinated Loss for Autonomous Mobility-on-Demand Fleet Control
Zeno Woywood, Jasper I. Wiltfang, Julius Luy +2
We study a sequential decision-making problem for a profit-maximizing operator of an autonomous mobility-on-demand system. Optimizing a central operator's vehicle-to-request dispat…
Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution Shifts
Tobias Enders, James Harrison, Maximilian Schiffer
We study the robustness of deep reinforcement learning algorithms against distribution shifts within contextual multi-stage stochastic combinatorial optimization problems from the…
Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
Heiko Hoppe, Tobias Enders, Quentin Cappart +1
We study vehicle dispatching in autonomous mobility on demand (AMoD) systems, where a central operator assigns vehicles to customer requests or rejects these with the aim of maximi…