著者

中嶋 宏 森島 泰則 山田 亮太 Scott Brave Heidy Maldonado Clifford Nass 川路 茂保

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.19, no.3, pp.184-196, 2004 (Released:2004-04-06)

参考文献数

29

被引用文献数

4 15

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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.

著者

中嶋 宏 森島 泰則 山田 亮太 Scott Brave Heidy Maldonado Clifford Nass 川路 茂保

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.19, pp.184-196, 2004-11-01

被引用文献数

1 15

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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.

著者

島川 はる奈 山田 亮太 森谷 俊洋 乾 和志

出版者

日本知能情報ファジィ学会

雑誌

知能と情報 : 日本知能情報ファジィ学会誌 : journal of Japan Society for Fuzzy Theory and Intelligent Informatics (ISSN:13477986)

巻号頁・発行日

vol.20, no.4, pp.591-600, 2008-08-15

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近年,日本ではマザー工場制を採用している企業が増えている.マザー工場制とは,メーカーが海外生産子会社に対して技術支援を展開する際,そのモデル工場となる本国工場が窓口ないしは担当工場となり,現地にあるサテライト工場に適した技術者や管理者を派遣し,現場指導を展開する人材派遣を中心とした技術支援方法である.サテライト工場で生産した製品に不具合が発生し,その原因が現場担当者では判断できない場合,本国にいるマザー工場の熟練者に出張を依頼した上で不具合を解消してもらう必要がある.このため,マザー工場の熟練者の出張費かかさみ,莫大なコストが必要となる.また,熟練者がサテライト工場に到着するまで不具合が放置されてしまう.更に,熟練者を長時間拘束することで,生産性の低下にもつながってしまう.そこで我々は,オンラインノウハウ伝承システムを開発した.これは,遠隔コミュニケーションの基盤技術であるSOBAフレームワークと,暗黙知を形式知化することができる知識管理システムを利用したものである.本稿では,オンラインノウハウ伝承システムの導入によって,どれくらいの効果が得られるかを検証する.