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20172024
most citedSafe Reinforcement Learning Using Robust MPC

341 citations · 769 across the 30 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

eess.SY2019★ 2 cited

Towards Safe Reinforcement Learning Using NMPC and Policy Gradients: Part I - Stochastic case

Sebastien Gros, Mario Zanon

We present a methodology to deploy the stochastic policy gradient method, using actor-critic techniques, when the optimal policy is approximated using a parametric optimization pro…

eess.SY2019★ 6 cited

Towards Safe Reinforcement Learning Using NMPC and Policy Gradients: Part II - Deterministic Case

Sebastien Gros, Mario Zanon

In this paper, we present a methodology to deploy the deterministic policy gradient method, using actor-critic techniques, when the optimal policy is approximated using a parametri…

eess.SY2019★ 341 cited

Safe Reinforcement Learning Using Robust MPC

Mario Zanon, Sébastien Gros

Reinforcement Learning (RL) has recently impressed the world with stunning results in various applications. While the potential of RL is now well-established, many critical aspects…

eess.SY2019

Practical Reinforcement Learning of Stabilizing Economic MPC

Mario Zanon, Sébastien Gros, Alberto Bemporad

Reinforcement Learning (RL) has demonstrated a huge potential in learning optimal policies without any prior knowledge of the process to be controlled. Model Predictive Control (MP…

eess.SY2019★ 272 cited

Data-driven Economic NMPC using Reinforcement Learning

Sébastien Gros, Mario Zanon

Reinforcement Learning (RL) is a powerful tool to perform data-driven optimal control without relying on a model of the system. However, RL struggles to provide hard guarantees on…

eess.SY2019

Real-Time Constrained Trajectory Planning and Vehicle Control for Proactive Autonomous Driving With Road Users

Ivo Batkovic, Mario Zanon, Mohammad Ali +1

For motion planning and control of autonomous vehicles to be proactive and safe, pedestrians' and other road users' motions must be considered. In this paper, we present a vehicle…

math.OC2019★ 21 cited

A Parallel Decomposition Scheme for Solving Long-Horizon Optimal Control Problems

Sungho Shin, Timm Faulwasser, Mario Zanon +1

We present a temporal decomposition scheme for solving long-horizon optimal control problems. In the proposed scheme, the time domain is decomposed into a set of subdomains with pa…