@inproceedings{9e485e803f92466d8131847b22e8e946,
title = "Comparisons of continuous-time and discrete-time Q-learning schemes for adaptive linear quadratic control",
abstract = "In this paper, we compare two online model-free Q-learning schemes for adaptive linear quadratic (LQ) control of discrete-time (DT) and continuous-time (CT) dynamical systems. Both Q-learning schemes come from the optimality principles, but the DT and CT g-learning is designed with different β-functions. This difference may results in the different exploration properties and convergence speeds. Numerical simulations with an ideal DC motor are carried out to further investigate and compare the Q-learning methods.",
keywords = "LQR, g-learning, policy iteration, reinforcement learning",
author = "Chun, {Tae Yoon} and Lee, {Jae Young} and Park, {Jin Bae} and Choi, {Yoon Ho}",
year = "2012",
language = "English",
isbn = "9781467322591",
series = "Proceedings of the SICE Annual Conference",
publisher = "Society of Instrument and Control Engineers (SICE)",
pages = "1228--1233",
booktitle = "2012 Proceedings of SICE Annual Conference, SICE 2012",
note = "2012 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan, SICE 2012 ; Conference date: 20-08-2012 Through 23-08-2012",
}