Self-improving empathy learning

Roberto Legaspi, Satoshi Kurihara, Ken Ichi Fukui, Koichi Moriyama, Masayuki Numao

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

Studies have emphasized that empathy is a learnable skill that can be developed through learning from experience. Applying this in the context of human-system interaction, an empathic system is one that automatically acquires an initial knowledge of empathy that is permitted to be incomplete, hence inaccurate and imperfect, but improves this knowledge each time it learns from its interactions with the user until its empathy knowledge matures over time. This paper posits a self-improving empathy learning for user-centric systems. Due to the nature of the problem that centers on incremental experiential learning, this problem becomes a machine learning application. We highlight the need for machine learning techniques that can address the challenge of an empathic system self-improving its empathy model efficiently online from incomplete knowledge through the intelligent use of its experiences. We suggest that the community position itself to investigate empathic reasoning in the context of a self-learning system with machine learning at the core of its AI.

本文言語English
ホスト出版物のタイトル5th International Conference on Information Technology and Applications, ICITA 2008
ページ88-93
ページ数6
出版ステータスPublished - 2008 12 1
外部発表はい
イベント5th International Conference on Information Technology and Applications, ICITA 2008 - Cairns, QLD, Australia
継続期間: 2008 6 232008 6 26

出版物シリーズ

名前5th International Conference on Information Technology and Applications, ICITA 2008

Other

Other5th International Conference on Information Technology and Applications, ICITA 2008
国/地域Australia
CityCairns, QLD
Period08/6/2308/6/26

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用
  • 情報システム
  • ソフトウェア

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