Title :
A group emotion control system based on reinforcement learning
Author :
Kee-Hoon Kim;Sung-Bae Cho
Author_Institution :
Department of Computer Science, Yonsei University, Seoul, Republic of Korea
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.
Keywords :
"Learning (artificial intelligence)","Control systems","Temperature sensors","Image color analysis","Markov processes","Real-time systems","Brain modeling"
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2015 7th International Conference of
DOI :
10.1109/SOCPAR.2015.7492826