Abstract
Recently, ubiquitous computing and related sensor technology have significantly progressed. On the other side, the relationship between human emotion and sensory stimuli has been investigated. With this background, we propose sensory stimuli control system to adjust group emotion to given target emotion. Valence-arousal model was adapted for defining group emotion, and survey of 73-papers and onsite-investigation had done for domain knowledge. The proposed system is based on the partially observable Markov decision process to deal with the uncertain states of group emotion, and reinforcement learning approach to learn the criterion of decision in real time. To evaluate the proposed system, we collected 160-minutes data from kindergarten where the music and math classes are ongoing with 10 prescholers and 1 caregiver are participating. Our system produced 55.17% of accuracy, which outperfomed the original system by 15.51%p.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 |
| Editors | Mario Koppen, Azah Kamilah Muda, Kun Ma, Bing Xue, Hideyuki Takagi, Ajith Abraham |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 303-307 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781467393607 |
| DOIs | |
| Publication status | Published - 2016 Jun 15 |
| Event | 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 - Fukuoka, Japan Duration: 2015 Nov 13 → 2015 Nov 15 |
Publication series
| Name | Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 |
|---|
Other
| Other | 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 |
|---|---|
| Country | Japan |
| City | Fukuoka |
| Period | 15/11/13 → 15/11/15 |
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All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Signal Processing
- Control and Optimization
- Modelling and Simulation
Cite this
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A group emotion control system based on reinforcement learning. / Kim, Kee Hoon; Cho, Sung Bae.
Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015. ed. / Mario Koppen; Azah Kamilah Muda; Kun Ma; Bing Xue; Hideyuki Takagi; Ajith Abraham. Institute of Electrical and Electronics Engineers Inc., 2016. p. 303-307 7492826 (Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A group emotion control system based on reinforcement learning
AU - Kim, Kee Hoon
AU - Cho, Sung Bae
PY - 2016/6/15
Y1 - 2016/6/15
N2 - Recently, ubiquitous computing and related sensor technology have significantly progressed. On the other side, the relationship between human emotion and sensory stimuli has been investigated. With this background, we propose sensory stimuli control system to adjust group emotion to given target emotion. Valence-arousal model was adapted for defining group emotion, and survey of 73-papers and onsite-investigation had done for domain knowledge. The proposed system is based on the partially observable Markov decision process to deal with the uncertain states of group emotion, and reinforcement learning approach to learn the criterion of decision in real time. To evaluate the proposed system, we collected 160-minutes data from kindergarten where the music and math classes are ongoing with 10 prescholers and 1 caregiver are participating. Our system produced 55.17% of accuracy, which outperfomed the original system by 15.51%p.
AB - Recently, ubiquitous computing and related sensor technology have significantly progressed. On the other side, the relationship between human emotion and sensory stimuli has been investigated. With this background, we propose sensory stimuli control system to adjust group emotion to given target emotion. Valence-arousal model was adapted for defining group emotion, and survey of 73-papers and onsite-investigation had done for domain knowledge. The proposed system is based on the partially observable Markov decision process to deal with the uncertain states of group emotion, and reinforcement learning approach to learn the criterion of decision in real time. To evaluate the proposed system, we collected 160-minutes data from kindergarten where the music and math classes are ongoing with 10 prescholers and 1 caregiver are participating. Our system produced 55.17% of accuracy, which outperfomed the original system by 15.51%p.
UR - http://www.scopus.com/inward/record.url?scp=84979297322&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979297322&partnerID=8YFLogxK
U2 - 10.1109/SOCPAR.2015.7492826
DO - 10.1109/SOCPAR.2015.7492826
M3 - Conference contribution
AN - SCOPUS:84979297322
T3 - Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
SP - 303
EP - 307
BT - Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
A2 - Koppen, Mario
A2 - Muda, Azah Kamilah
A2 - Ma, Kun
A2 - Xue, Bing
A2 - Takagi, Hideyuki
A2 - Abraham, Ajith
PB - Institute of Electrical and Electronics Engineers Inc.
ER -