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2016 | OriginalPaper | Buchkapitel

A Sensory Control System for Adjusting Group Emotion Using Bayesian Networks and Reinforcement Learning

verfasst von : Jun-Ho Kim, Ki-Hoon Kim, Sung-Bae Cho

Erschienen in: Hybrid Artificial Intelligent Systems

Verlag: Springer International Publishing

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Abstract

The relationship between sensory stimuli and emotion has been actively investigated, but it is relatively undisclosed to determine appropriate stimuli for inducing the target emotion for a group of people in the same space like school, hospital, store, etc. In this paper, we propose a stimuli control system to adjust group emotion in a closed space, especially kindergarten. The proposed system predicts the next emotion of a group of people using modular tree-structured Bayesian networks, and controls the stimuli appropriate to the target emotion using utility table initialized by domain knowledge and adapted by reinforcement learning as the cases of stimuli and emotions are cumulated. To evaluate the proposed system, the real data were collected for five days from a kindergarten where the sensor and stimulus devices were installed. We obtained 84 % of prediction accuracy, and 56.2 % of stimuli control accuracy. Moreover, in the scenario tests on math and music classes, we could control the stimuli to fit the target emotion with 63.2 % and 76.3 % accuracies, respectively.

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Metadaten
Titel
A Sensory Control System for Adjusting Group Emotion Using Bayesian Networks and Reinforcement Learning
verfasst von
Jun-Ho Kim
Ki-Hoon Kim
Sung-Bae Cho
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-32034-2_32