2 citations · 3 across the 4 of their papers we have counts for
4 papers
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…
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…
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…