loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Author: Kary Främling

Affiliation: Helsinki University of Technology, Finland

Keyword(s): Linear function approximation, Gradient descent, Learning rate, Reinforcement learning, Light-seeking robot.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications ; Neural Networks Based Control Systems

Abstract: Adaptive behaviour through machine learning is challenging in many real-world applications such as robotics. This is because learning has to be rapid enough to be performed in real time and to avoid damage to the robot. Models using linear function approximation are interesting in such tasks because they offer rapid learning and have small memory and processing requirements. Adalines are a simple model for gradient descent learning with linear function approximation. However, the performance of gradient descent learning even with a linear model greatly depends on identifying a good value for the learning rate to use. In this paper it is shown that the learning rate should be scaled as a function of the current input values. A scaled learning rate makes it possible to avoid weight oscillations without slowing down learning. The advantages of using the scaled learning rate are illustrated using a robot that learns to navigate towards a light source. This light-seeking robot performs a Reinforcement Learning task, where the robot collects training samples by exploring the environment, i.e. taking actions and learning from their result by a trial-and-error procedure. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.189.180.76

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Främling, K. (2004). SCALED GRADIENT DESCENT LEARNING RATE - Reinforcement learning with light-seeking robot. In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 972-8865-12-0; ISSN 2184-2809, SciTePress, pages 3-11. DOI: 10.5220/0001138600030011

@conference{icinco04,
author={Kary Främling.},
title={SCALED GRADIENT DESCENT LEARNING RATE - Reinforcement learning with light-seeking robot},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2004},
pages={3-11},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001138600030011},
isbn={972-8865-12-0},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - SCALED GRADIENT DESCENT LEARNING RATE - Reinforcement learning with light-seeking robot
SN - 972-8865-12-0
IS - 2184-2809
AU - Främling, K.
PY - 2004
SP - 3
EP - 11
DO - 10.5220/0001138600030011
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic