23 citations · 47 across the 10 of their papers we have counts for
12 papers
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…
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…
Optimal Management of the Peak Power Penalty for Smart Grids Using MPC-based Reinforcement Learning
Wenqi Cai, Hossein N. Esfahani, Arash B. Kordabad +1
The cost of the power distribution infrastructures is driven by the peak power encountered in the system. Therefore, the distribution network operators consider billing consumers b…
Multi-agent Battery Storage Management using MPC-based Reinforcement Learning
A. Bahari Kordabad, W. Cai, S. Gros
In this paper, we present the use of Model Predictive Control (MPC) based on Reinforcement Learning (RL) to find the optimal policy for a multi-agent battery storage system. A time…
MPC-based Reinforcement Learning for a Simplified Freight Mission of Autonomous Surface Vehicles
Wenqi Cai, Arash B. Kordabad, Hossein N. Esfahani +2
In this work, we propose a Model Predictive Control (MPC)-based Reinforcement Learning (RL) method for Autonomous Surface Vehicles (ASVs). The objective is to find an optimal polic…
Verification of Dissipativity and Evaluation of Storage Function in Economic Nonlinear MPC using Q-Learning
Arash Bahari Kordabad, Sebastien Gros
In the Economic Nonlinear Model Predictive (ENMPC) context, closed-loop stability relates to the existence of a storage function satisfying a dissipation inequality. Finding the st…
Approximate Robust NMPC using Reinforcement Learning
Hossein Nejatbakhsh Esfahani, Arash Bahari Kordabad, Sebastien Gros
We present a Reinforcement Learning-based Robust Nonlinear Model Predictive Control (RL-RNMPC) framework for controlling nonlinear systems in the presence of disturbances and uncer…
Bias Correction in Deterministic Policy Gradient Using Robust MPC
Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Sebastien Gros
In this paper, we discuss the deterministic policy gradient using the Actor-Critic methods based on the linear compatible advantage function approximator, where the input spaces ar…
MPC-based Reinforcement Learning for Economic Problems with Application to Battery Storage
Arash Bahari Kordabad, Wenqi Cai, Sebastien Gros
In this paper, we are interested in optimal control problems with purely economic costs, which often yield optimal policies having a (nearly) bang-bang structure. We focus on polic…
Reinforcement Learning based on MPC/MHE for Unmodeled and Partially Observable Dynamics
Hossein Nejatbakhsh Esfahani, Arash Bahari Kordabad, Sebastien Gros
This paper proposes an observer-based framework for solving Partially Observable Markov Decision Processes (POMDPs) when an accurate model is not available. We first propose to use…
Reinforcement Learning based on Scenario-tree MPC for ASVs
Arash Bahari Kordabad, Hossein Nejatbakhsh Esfahani, Anastasios M. Lekkas +1
In this paper, we present the use of Reinforcement Learning (RL) based on Robust Model Predictive Control (RMPC) for the control of an Autonomous Surface Vehicle (ASV). The RL-MPC…