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Found 4 papers, 0 papers with code
Optimal Transport for Correctional Learning
In this framework, an expert agent, referred to as the teacher, modifies the data used by a learning agent, known as the student, to improve its estimation process.
A Teacher-Student Markov Decision Process-based Framework for Online Correctional Learning
A classical learning setting typically concerns an agent/student who collects data, or observations, from a system in order to estimate a certain property of interest.
Learning Models of Model Predictive Controllers using Gradient Data
As a proof of concept, we apply this approach to explicit MPC (eMPC), for which the feedback law is a piece-wise affine function of the state, but the number of pieces grows rapidly with the state dimension.
On Training and Evaluation of Neural Network Approaches for Model Predictive Control
The contribution of this paper is a framework for training and evaluation of Model Predictive Control (MPC) implemented using constrained neural networks.
