activity
20172026
most citedDeep Reinforcement Learning amidst Lifelong Non-Stationarity

26 citations · 59 across the 11 of their papers we have counts for

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Showing eess.SYShow all

5 papers · 1 filter

eess.SY2022

Adaptive Robust Model Predictive Control via Uncertainty Cancellation

Rohan Sinha, James Harrison, Spencer M. Richards +1

We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally…

eess.SY20221 cited

Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand

Daniele Gammelli, Kaidi Yang, James Harrison +3

Autonomous Mobility-on-Demand (AMoD) systems represent an attractive alternative to existing transportation paradigms, currently challenged by urbanization and increasing travel ne…

eess.SY2021

Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems

Daniele Gammelli, Kaidi Yang, James Harrison +3

Autonomous mobility-on-demand (AMoD) systems represent a rapidly developing mode of transportation wherein travel requests are dynamically handled by a coordinated fleet of robotic…

eess.SY2021

Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty

Rohan Sinha, James Harrison, Spencer M. Richards +1

We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally…

eess.SY2021

Particle MPC for Uncertain and Learning-Based Control

Robert Dyro, James Harrison, Apoorva Sharma +1

As robotic systems move from highly structured environments to open worlds, incorporating uncertainty from dynamics learning or state estimation into the control pipeline is essent…