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Found 4 papers, 1 papers with code
RAPID: Autonomous Multi-Agent Racing using Constrained Potential Dynamic Games
Namely, we show that our racing game is an instance of a constrained dynamic potential game.
Pricing for Multi-modal Pickup and Delivery Problems with Heterogeneous Users
In this paper we study the pickup and delivery problem with multiple transportation modalities, and address the challenge of efficiently allocating transportation resources while price matching users with their desired delivery modes.
Learning to Influence Vehicles' Routing in Mixed-Autonomy Networks by Dynamically Controlling the Headway of Autonomous Cars
We train an RL policy that learns to regulate the headway of autonomous cars such that the total travel time in the network is minimized.
Learning Contraction Policies from Offline Data
We then learn both the control policy and the contraction metric such that the distance between the trajectories from the offline data set and our generated auxiliary sample trajectories decreases over time.
