Paper Abstract and Keywords |
Presentation |
2018-07-12 15:05
[Tutorial Lecture]
Reinforcement Learning: Application and Issues Takaki Makino (Google) RCC2018-51 NS2018-68 RCS2018-113 SR2018-48 ASN2018-45 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement learning is a machine learning framework that learns best sequence of actions through trial-and-error in domains where providing sufficient supervised data is infeasible. Despite its success recently attracts a lot of attentions, it is not easy to apply it to a new problem. In this tutorial, we introduce the basic idea of reinforcement learning and explain types of problems that are suitable to reinforcement learning. In addition, we discuss roadblocks and recent techniques, in particular the part of problem formulation, reward design and deep reinforcement learning. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
reinforcement learning / machine learning / deep reinforcement learning / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 126, SR2018-48, pp. 129-129, July 2018. |
Paper # |
SR2018-48 |
Date of Issue |
2018-07-04 (RCC, NS, RCS, SR, ASN) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
RCC2018-51 NS2018-68 RCS2018-113 SR2018-48 ASN2018-45 |
Conference Information |
Committee |
ASN NS RCS SR RCC |
Conference Date |
2018-07-11 - 2018-07-13 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Hakodate Arena |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc. |
Paper Information |
Registration To |
SR |
Conference Code |
2018-07-ASN-NS-RCS-SR-RCC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Reinforcement Learning: Application and Issues |
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reinforcement learning |
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machine learning |
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deep reinforcement learning |
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1st Author's Name |
Takaki Makino |
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Google Inc. (Google) |
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Speaker |
Author-1 |
Date Time |
2018-07-12 15:05:00 |
Presentation Time |
120 minutes |
Registration for |
SR |
Paper # |
RCC2018-51, NS2018-68, RCS2018-113, SR2018-48, ASN2018-45 |
Volume (vol) |
vol.118 |
Number (no) |
no.123(RCC), no.124(NS), no.125(RCS), no.126(SR), no.127(ASN) |
Page |
p.119(RCC), p.151(NS), p.161(RCS), p.129(SR), p.135(ASN) |
#Pages |
1 |
Date of Issue |
2018-07-04 (RCC, NS, RCS, SR, ASN) |
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