Paper Abstract and Keywords |
Presentation |
2013-03-13 14:35
Hebbian learning of transition probabilities
-- a neural network study -- Hiroshi Saito, Ken Takiyama (Univ. of Tokyo), Masato Okada (Univ. of Tokyo/RIKEN) NC2012-145 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
State of the environment changes on and on, and humans animals predict future state through their experiences. Recent brain imaging study suggested that the transition probabilities between two states are encoded in the brain. However, it is controversial how neural networks of the brain learn the transition probabilities. We propose a Hebbian learning algorithm and show a neural network model can learn the transition probabilities by this learning. Our model neuron shows similar activity to those of observed in monkey LIP neurons in random dots motion discrimination tasks. We also show that the eligibility trace which is supposed to be implemented in the brain gives our network extra positive effects. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Hebb rule / neural network model / transition probabilities / eligibility trace / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 480, NC2012-145, pp. 67-72, March 2013. |
Paper # |
NC2012-145 |
Date of Issue |
2013-03-06 (NC) |
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 |
NC2012-145 |
Conference Information |
Committee |
MBE NC |
Conference Date |
2013-03-13 - 2013-03-15 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Tamagawa University |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
|
Paper Information |
Registration To |
NC |
Conference Code |
2013-03-MBE-NC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Hebbian learning of transition probabilities |
Sub Title (in English) |
a neural network study |
Keyword(1) |
Hebb rule |
Keyword(2) |
neural network model |
Keyword(3) |
transition probabilities |
Keyword(4) |
eligibility trace |
Keyword(5) |
|
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Hiroshi Saito |
1st Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Ken Takiyama |
2nd Author's Affiliation |
The University of Tokyo (Univ. of Tokyo) |
3rd Author's Name |
Masato Okada |
3rd Author's Affiliation |
The University of Tokyo/RIKEN (Univ. of Tokyo/RIKEN) |
4th Author's Name |
|
4th Author's Affiliation |
() |
5th Author's Name |
|
5th Author's Affiliation |
() |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-1 |
Date Time |
2013-03-13 14:35:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2012-145 |
Volume (vol) |
vol.112 |
Number (no) |
no.480 |
Page |
pp.67-72 |
#Pages |
6 |
Date of Issue |
2013-03-06 (NC) |