CONFERENCE SCHEDULE AND PROGRAM
- Time table(20220825) is here!
- Access to the Venue is here.
- Special events for participants on August 23. (Invitation Only)
- Banquet(August 25) is here.
【Banquiet】MLB café TOKYO TOKYO DOME CITY（URL）
Kouraku 1-3-61, Tokyo Dome City Crystal Avenue. Bunkyo-ku, Tokyo 112-8575
By train: 6-minute walk from JR, Tokyo Metro Suidobashi Station
By car: 5 minutes from Iidabashi, Ikebukuro Line-, Tokyo Expressway
Access to the Venue
- Toyo University, Hakusan Campus
- Building No.1, 3rd Floor
Professor Takayuki Ito (Kyoto University)
Brief CV: Dr. Takayuki ITO is Professor of Kyoto University. He received the B.E., M.E, and Doctor of Engineering from the Nagoya Institute of Technology in 1995, 1997, and 2000, respectively. From 1999 to 2001, he was a research fellow of the Japan Society for the Promotion of Science (JSPS). From 2000 to 2001, he was a visiting researcher at USC/ISI (University of Southern California/Information Sciences Institute). From April 2001 to March 2003, he was an associate professor of Japan Advanced Institute of Science and Technology (JAIST). From April 2004 to March 2013, he was an associate professor of Nagoya Institute of Technology. From April 2014 to September 2020, he was a professor of Nagoya Institute of Technology. From October 2020, he is a professor of Kyoto University. From 2005 to 2006, he is a visiting researcher at Division of Engineering and Applied Science, Harvard University and a visiting researcher at the Center for Coordination Science, MIT Sloan School of Management. From 2008 to 2010, he was a visiting researcher at the Center for Collective Intelligence, MIT Sloan School of Management. From 2017 to 2018, he is a invited researcher of Artificial Intelligence Center of AIST, JAPAN. From March 5, 2019, he is the CTO of AgreeBit, inc. He is a board member of IFAAMAS, Executive Committee Member of IEEE Computer Society Technical Committee on Intelligent Informatics, the PC-chair of AAMAS2013, PRIMA2009, the Local Arrangements Chair of IJCAI-PRICAI2020, General-Chair of PRIMA2014, and was a SPC/PC member in many top-level conferences (IJCAI, AAMAS, ECAI, AAAI, etc). He received the JSAI (Japan Society for Artificial Intelligence) Contribution Award, the JSAI Achievement Award, the JSPS Prize, 2014, the Prize for Science and Technology (Research Category), The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology, 2013, the Young Scientists' Prize, The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology, 2007, the Nagao Special Research Award of the Information Processing Society of Japan, 2007, the Best Paper Award of AAMAS2006, the 2005 Best Paper Award from Japan Society for Software Science and Technology, the Best Paper Award in the 66th annual conference of 66th Information Processing Society of Japan, and the Super Creator Award of 2004 IPA Exploratory Software Creation Projects. He is Principle Investigator of the Japan Cabinet Funding Program for Next Generation World-Leading Researchers (NEXT Program). Further, he has several companies, which are handling web-based systems and enterprise distributed systems. His main research interests include multi-agent systems, intelligent agents, collective intelligence, group decision support system, etc.
Title: Towards Hyper-democracy: An Agent that Facilitates Crowd Discussion
Abstract: Online discussion among civilian is important and essential for next-generation democracy. Providing good support is critical for establishing and maintaining coherent discussions. Large-scale online discussion platforms are receiving great attention as potential next-generation methods for smart democratic citizen platforms. Such platforms require support functions that can efficiently achieve a consensus, reasonably integrate ideas, and discourage flaming. Researchers are developing several crowd-scale discussion platforms and conducting social experiments with a local government. One of these studies employed human facilitators in order to achieve good discussion. However, they clarified the critical problem faced by human facilitators caused by the difficulty of facilitating large-scale online discussions. In this work, we propose an automated facilitation agent to manage crowd-scale online discussions. An automated facilitator agent extracts the discussion structure from the texts posted in discussions by people. We conducted a large-scale social experiment with Nagoya City’s local government.