人間‐機械協調システムにおける社会的知性―心のモデルとパーソナリティによるエージェントの社会的応答について―

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  • 中嶋 宏
    オムロン株式会社　技術本部コントロール研究所
  • 森島 泰則
    国際基督教大学　教養学部
  • 山田 亮太
    オムロン株式会社　技術本部コントロール研究所
  • Scott Brave
    Stanford University, Department of Communication and Kozmetsky Global Collaboratory.
  • Heidy Maldonado
    Stanford University, School of Education.
  • Clifford Nass
    Stanford University, Department of Communication and Kozmetsky Global Collaboratory.
  • 川路 茂保
    熊本大学　大学院自然科学研究科システム情報科学専攻

書誌事項

タイトル別名
  • Social Intelligence in a Human-Machine Collaboration System-Social Responses of Agents with Mind Model and Personality
  • 人間-機械協調システムにおける社会的知性--心のモデルとパーソナリティによるエージェントの社会的応答について
  • ニンゲン キカイ キョウチョウ システム ニ オケル シャカイテキ チセイ ココロ ノ モデル ト パーソナリティ ニ ヨル エージェント ノ シャカイテキ オウトウ ニ ツイテ
  • Social Responses of Agents with Mind Model and Personality
  • 心のモデルとパーソナリティによるエージェントの社会的応答について

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説明

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

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