Estimation of Hierarchical Emotion in Mental State Transition Learning Network

URI http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/5174
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Title
Estimation of Hierarchical Emotion in Mental State Transition Learning Network
Author
氏名 ICHIMURA Takumi
ヨミ イチムラ タクミ
別名 市村 匠
氏名 MERA Kazuya
ヨミ メラ カズヤ
別名 目良 和也
Abstract

In general, emotions are often appeared in the facial expressions, voice pitch, exaggerated gesticulation, and so on. They are outward signals of emotions, internal world in order to serve for human communications. Perlovsky described on aesthetic emotions and analyzed their role within joint functioning of cognition and language. This paper proposes the different method from his idea. The method uses Mental State Transition Network proposed by Ren and Emotion Generation Calculations. Moreover, the transition costs in the network are modified according to the stimulus from external world.
The simulation results also are reported.

Description Peer Reviewed
Journal Title
Proceedings : 5th International Workshop on Computational Intelligence & Applications (IWCIA 2009) : November 10-12, 2009, Hiroshima, Japan
Spage
35
Epage
40
Published Date
2009-11
Publisher
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
NCID
BB00577064
Language
eng
NIIType
Conference Paper
Text Version
出版社版
Rights
©Copyright by IEEE SMC Hiroshima Chapter 2009. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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hiroshima-cu