Toward Better Integration of Efficient Access Platform for Open Data and Fast Multiagent-based Simulation Techniques

2016 Fiscal Year Final Research Report

• Project/Area Number: 26540162
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Web informatics, Service informatics
• Research Institution: Shizuoka University
• Principal Investigator: Fukuta Naoki 静岡大学, 情報学部, 准教授 (30345805)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: オープンデータ / セマンティックウェブ / マルチエージェントシミュレーション / メカニズムデザイン / アルゴリズム

Outline of Final Research Achievements

In this research, we have tackled the central issues about utilizing ontology-based and inter-linking open data (Linked Open Data, LOD). The research focused on better utilization and approximation of ontology-based reasoning on retrieving such LODs by applying evolutionary algorithms and machine learning techniques. Furthermore, the research also aimed to realize better approximations on resource allocation mechanisms such as combinatorial auctions, which could be applied on various complex social simulations. Also this research developed a framework to efficiently configure and run such complex simulations on GPUs and other multi-core devices by developing and applying Budget-Limited Multi-Armed Bandit algorithms. The outcome of this research was constructed from 7 papers published from international and domestic journals or magazines, and 16 presentations at international and domestic conferences including 2 invited talks on international conferences or symposiums.

Free Research Field

知能情報学