Preference Elicitation and Issue Structurization for Multi-agent Automated Negotiations

2017 Fiscal Year Final Research Report

• Project/Area Number: 26730116
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Intelligent informatics
• Research Institution: Tokyo University of Agriculture and Technology
• Principal Investigator: Fujita Katsuhide 東京農工大学, 工学(系)研究科(研究院), 准教授 (00625676)
• Project Period (FY): 2014-04-01 – 2018-03-31
• Keywords: マルチエージェントシステム / 自動交渉 / 深層学習

Outline of Final Research Achievements

We proposed the method of structuring issue-dependencies automatically and extracting the users' preferences effectively. In addition, we proposed automated negotiation protocols considering the extracted issue-dependencies and users' preferences. Our outcomes are "Compromising Negotiation Strategy using Analytic Hierarchy Process," "Effective Automated Negotiations based on Recursive Partitioning by Issue Dendrogram," "Prediction of Nash Bargaining Solution by Deep Learning for Negotiation Dialogue," and "Argument Mining for Discussion Threads based on Parallel Constrained Pointer Architecture." Our research can be proceeded as I planned generally, and achieved research goals.

Free Research Field

人工知能