{"id":1447,"date":"2020-04-03T13:41:33","date_gmt":"2020-04-03T04:41:33","guid":{"rendered":"https:\/\/sr.sfc.keio.ac.jp\/www\/?p=1447"},"modified":"2020-04-03T16:23:33","modified_gmt":"2020-04-03T07:23:33","slug":"%e6%97%a5%e6%9c%ac%e8%aa%9e-%e4%bc%9a%e8%a9%b1%e5%8f%82%e5%8a%a0%e8%80%85%e3%81%ae%e6%8c%af%e3%82%8b%e8%88%9e%e3%81%84%e3%82%92%e8%80%83%e6%85%ae%e3%81%97%e3%81%9f%e8%a4%87%e6%95%b0%e4%bc%9a","status":"publish","type":"post","link":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/project\/1447\/","title":{"rendered":"Implementation and Evaluation of Multi-Conversation Scheduler Considering Participants\u2019 Social Behavior\uff1atheramin"},"content":{"rendered":"When a robot is working in a public space, because multiple users behave according to their own purpose, robots can have multiple tasks at the same time. For example, a conversation can interrupt another conversation. A robot should suspend the current conversation when a third person calls the robot which is already talking with another user, or to greet in a situation that a friend is passing by the robot. In this study, I designed a robot behavior in the situation that the interrupter expected to have a new conversation with the robot. Traditional conversational-interruption studies have aimed the interruptions as a cooperative interaction within the current conversation, but few studies have aimed at interruption from outside of the conversation. For a robot to handle interruptions, it is necessary to detect interruption during a conversation, prioritize conversations, and build consensus with users within the conversation. CACTS-C not only schedules conversations based on the four factors, conversation length, relation between the interrupter and the interrupted person, tasks of the stakeholders, and emotion at interruption, but also holds a consensus building conversation with a person who will wait for the robot until the prioritized conversation ends. I implemented a robot-conversation system using CACTSC. The conversation scenario was written in AIML-ap, which is uniquely expanded AIML (Artificial Intelligence Markup Language), which is a markup language for chatbot, to describe the conversation scenario in adjacent pair units. I evaluated the behaviors of the implemented robot and discussed the effectiveness of the model of the CACTS-C\u2019s scheduler. Experimentation results revealed that the conversation prioritization has effectiveness in conversation scheduling. In addition, the persuasion behavior of CACTS-C made the impression of robot\u2019s fairness better than just stating the reason for interruption.","protected":false},"excerpt":{"rendered":"<p>When a robot is working in a public space, because multiple users behave according to their own purpose, robots can have multiple tasks at the same time. For example, a conversation can interrupt another conversation. A robot should suspend the current conversation when a third person calls the robot which is already talking with another user, or to greet in a situation that a friend is passing by the robot. In this study, I designed a robot behavior in the situation that the interrupter expected to have a new conversation with the robot. Traditional conversational-interruption studies have aimed the interruptions as a cooperative interaction within the current conversation, but few studies have aimed at interruption from outside of the conversation. For a robot to handle interruptions, it is necessary to detect interruption during a conversation, prioritize conversations, and build consensus with users within the conversation. CACTS-C not only schedules conversations based on the four factors, conversation length, relation between the interrupter and the interrupted person, tasks of the stakeholders, and emotion at interruption, but also holds a consensus building conversation with a person who will wait for the robot until the prioritized conversation ends. I implemented a robot-conversation system using CACTSC. The conversation scenario was written in AIML-ap, which is uniquely expanded AIML (Artificial Intelligence Markup Language), which is a markup language for chatbot, to describe the conversation scenario in adjacent pair units. I evaluated the behaviors of the implemented robot and discussed the effectiveness of the model of the CACTS-C\u2019s scheduler. Experimentation results revealed that the conversation prioritization has effectiveness in conversation scheduling. In addition, the persuasion behavior of CACTS-C made the impression of robot\u2019s fairness better than just stating the reason for interruption.<\/p>\n","protected":false},"author":9,"featured_media":1449,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16,4],"tags":[],"class_list":["post-1447","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-16","category-project"],"_links":{"self":[{"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/posts\/1447"}],"collection":[{"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/comments?post=1447"}],"version-history":[{"count":5,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/posts\/1447\/revisions"}],"predecessor-version":[{"id":1494,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/posts\/1447\/revisions\/1494"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/media\/1449"}],"wp:attachment":[{"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/media?parent=1447"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/categories?post=1447"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sr.sfc.keio.ac.jp\/www\/en\/wp-json\/wp\/v2\/tags?post=1447"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}