9 citations · 12 across the 6 of their papers we have counts for
6 papers
Exponential stability of the linearized viscous Saint-Venant equations using a quadratic Lyapunov function
Amaury Hayat, Nathan Lichtlé
In this work, we investigate the exponential stability of the viscous Saint-Venant equations by adding to the standard hyperbolic Saint-Venant equations a viscosity term coming fro…
Reevaluating Policy Gradient Methods for Imperfect-Information Games
Max Rudolph, Nathan Lichtle, Sobhan Mohammadpour +6
In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information games, researchers have developed nu…
Traffic Smoothing Controllers for Autonomous Vehicles Using Deep Reinforcement Learning and Real-World Trajectory Data
Nathan Lichtlé, Kathy Jang, Adit Shah +3
Designing traffic-smoothing cruise controllers that can be deployed onto autonomous vehicles is a key step towards improving traffic flow, reducing congestion, and enhancing fuel e…
Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers
Jonathan W. Lee, George Gunter, Rabie Ramadan +25
This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular atten…
Optimizing Mixed Autonomy Traffic Flow With Decentralized Autonomous Vehicles and Multi-Agent RL
Eugene Vinitsky, Nathan Lichtle, Kanaad Parvate +1
We study the ability of autonomous vehicles to improve the throughput of a bottleneck using a fully decentralized control scheme in a mixed autonomy setting. We consider the proble…
Inter-Level Cooperation in Hierarchical Reinforcement Learning
Abdul Rahman Kreidieh, Glen Berseth, Brandon Trabucco +3
Hierarchies of temporally decoupled policies present a promising approach for enabling structured exploration in complex long-term planning problems. To fully achieve this approach…