@inproceedings{f68637deb0fb4a758c0636c385e1f15a,
title = "Transfer Learning Heuristically Accelerated Algorithm: A Case Study with Real Robots",
abstract = "Reinforcement Learning (RL) is a successful technique for learning the solutions of control problems from an agent's interaction in its domain. However, RL is known to be inefficient for real-world applications. In this paper we propose to use a combination of case-based reasoning (CBR) and heuristically accelerated reinforcement learning methods aiming to speed up a Reinforcement Learning algorithm in a transfer learning problem. We show results of applying this method on a robot soccer domain, where the use of the proposed method led to a significant improvement in the learning rate.",
keywords = "Heuristically Accelerated, Reinforcement Learning, Transfer Learning",
author = "Celiberto, {Luiz Antonio} and Bianchi, {Reinaldo A.C.} and Santos, {Paulo E.}",
year = "2016",
month = dec,
day = "15",
doi = "10.1109/LARS-SBR.2016.59",
language = "English",
series = "Proceedings - 13th Latin American Robotics Symposium and 4th Brazilian Symposium on Robotics, LARS/SBR 2016",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "311--316",
editor = "Cavalcante, {Sergio Vanderlei} and Flavio Tonidandel",
booktitle = "Proceedings - 13th Latin American Robotics Symposium and 4th Brazilian Symposium on Robotics, LARS/SBR 2016",
address = "United States",
note = "13th Latin American Robotics Symposium and 4th Brazilian Symposium on Robotics, LARS/SBR 2016 ; Conference date: 08-10-2016 Through 12-10-2016",
}