Paper Abstract and Keywords |
Presentation |
2020-03-06 11:20
Considering a human mobility model inspired by reinforcement learning Yuutaro Iwai, Akihiro Fujihara (CIT) IN2019-118 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement learning is a machine learning framework that
an agent repeatedly observes reward from environment as a
result of action to choose actions with high reward
expectations.
On the other hand, mobility models that satisfy the
statistical properties of human mobility patterns have been
proposed. However, a method of generating a mobility model
based on reinforcement learning has not been sufficiently
studied.
In this paper, a dataset containing mobility traces of taxi
cabs in San Francisco is used to propose a method of generating
a mobility model that learns action selection by giving rewards,
such as fare and gasoline charge, and also the distribution of
passengers' positions.
The $epsilon$-greedy method was used as the reinforcement
learning algorithm. The degree of learning was compared by
changing the search parameter $epsilon$. As a result, it was
found that the cumulative reward was highest when $epsilon=0$
because the taxi movement included an implicit search.
The generalization of the mobility model generation method
using reinforcement algorithm was also considered. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Human mobility models / Reinforcement learning / Data assimilation / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 461, IN2019-118, pp. 237-242, March 2020. |
Paper # |
IN2019-118 |
Date of Issue |
2020-02-27 (IN) |
ISSN |
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) |
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IN2019-118 |
Conference Information |
Committee |
NS IN |
Conference Date |
2020-03-05 - 2020-03-06 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Royal Hotel Okinawa Zanpa-Misaki |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
General |
Paper Information |
Registration To |
IN |
Conference Code |
2020-03-NS-IN |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Considering a human mobility model inspired by reinforcement learning |
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Human mobility models |
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Reinforcement learning |
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Data assimilation |
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1st Author's Name |
Yuutaro Iwai |
1st Author's Affiliation |
Chiba Institute of Technology (CIT) |
2nd Author's Name |
Akihiro Fujihara |
2nd Author's Affiliation |
Chiba Institute of Technology (CIT) |
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Speaker |
Author-1 |
Date Time |
2020-03-06 11:20:00 |
Presentation Time |
20 minutes |
Registration for |
IN |
Paper # |
IN2019-118 |
Volume (vol) |
vol.119 |
Number (no) |
no.461 |
Page |
pp.237-242 |
#Pages |
6 |
Date of Issue |
2020-02-27 (IN) |
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