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Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2 pp 215–226Cite as

Evolving Emotion Recognition Module for Intelligent Agent

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Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 2))

Abstract

An emotion recognition module is crucial in designing a computer agent that is capable of interacting with emotional expressions. Under-standing user’s current emotion can be achieved by several methods, but current researches are either using still images, or sensors that are not pervasive. Usual approach is using a generalized classifier to recognize pattern of emotion features captured by sensors. Unlike most researches, this research focuses on pervasive sensors and a single user, using evolution algorithm. This research also discusses about the classifier evolutions using Genetic Programming, and comparing several directed evolutions in evolving the emotion recognition module.

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References

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Author information

Authors and Affiliations

  1. Doshisha University, Kyoto, Japan

    Rahadian Yusuf, Ivan Tanev & Katsunori Shimohara

Authors
  1. Rahadian Yusuf
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  2. Ivan Tanev
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  3. Katsunori Shimohara
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Corresponding author

Correspondence to Rahadian Yusuf .

Editor information

Editors and Affiliations

  1. Faculty of Science and Technology Department of Infomatics, Kindai University, Higashi-Osaka, Japan

    Hisashi Handa

  2. Department of Computer Science and Intelligent Systems, Osaka Prefecture University, Osaka, Japan

    Hisao Ishibuchi

  3. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Yew-Soon Ong

  4. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Kay-Chen Tan

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Yusuf, R., Tanev, I., Shimohara, K. (2015). Evolving Emotion Recognition Module for Intelligent Agent. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_18

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  • DOI: https://doi.org/10.1007/978-3-319-13356-0_18

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13355-3

  • Online ISBN: 978-3-319-13356-0

  • eBook Packages: EngineeringEngineering (R0)

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