341 citations · 793 across the 35 of their papers we have counts for
8 papers · 1 filter
Conflict-free Charging and Real-time Control for an Electric Bus Network
Rémi Lacombe, Nikolce Murgovski, Sébastien Gros +1
The rapid adoption of electric buses by transit agencies around the world is leading to new challenges in the planning and operation of bus networks. In particular, the limited dri…
Equivalence of Optimality Criteria for Markov Decision Process and Model Predictive Control
Arash Bahari Kordabad, Mario Zanon, Sebastien Gros
This paper shows that the optimal policy and value functions of a Markov Decision Process (MDP), either discounted or not, can be captured by a finite-horizon undiscounted Optimal…
Solving Mission-Wide Chance-Constrained Optimal Control Using Dynamic Programming
Kai Wang, Sebastien Gros
This paper aims to provide a Dynamic Programming (DP) approach to solve the Mission-Wide Chance-Constrained Optimal Control Problems (MWCC-OCP). The mission-wide chance constraint…
Policy Gradient Reinforcement Learning for Uncertain Polytopic LPV Systems based on MHE-MPC
Hossein Nejatbakhsh Esfahani, Sebastien Gros
In this paper, we propose a learning-based Model Predictive Control (MPC) approach for the polytopic Linear Parameter-Varying (LPV) systems with inexact scheduling parameters (as e…
Bridging the gap between QP-based and MPC-based RL
Shambhuraj Sawant, Sebastien Gros
Reinforcement learning methods typically use Deep Neural Networks to approximate the value functions and policies underlying a Markov Decision Process. Unfortunately, DNN-based RL…
Interpretable Battery Cycle Life Range Prediction Using Early Degradation Data at Cell Level
Huang Zhang, Yang Su, Faisal Altaf +2
Battery cycle life prediction using early degradation data has many potential applications throughout the battery product life cycle. For that reason, various data-driven methods h…
Functional Stability of Discounted Markov Decision Processes Using Economic MPC Dissipativity Theory
Arash Bahari Kordabad, Sebastien Gros
This paper discusses the functional stability of closed-loop Markov Chains under optimal policies resulting from a discounted optimality criterion, forming Markov Decision Processe…
Quasi-Newton Iteration in Deterministic Policy Gradient
Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Wenqi Cai +1
This paper presents a model-free approximation for the Hessian of the performance of deterministic policies to use in the context of Reinforcement Learning based on Quasi-Newton st…