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Intelligent Software Lab
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A lab for agents and natural language processing, studying how to put artificial intelligence to work in society.
AboutAbout the lab
Putting artificial intelligence to work for society.
The Intelligent Software Lab studies how artificial intelligence technology can be used in society.
The lab has two pillars. One is multi-agent social simulation, which examines behavior in settings where multiple people or robots are present.
The other is natural language processing built around large language models, aiming for processing that goes into causal relationships and specialized knowledge.
With these two as twin pillars, the lab also pursues questions such as what intelligence is and what society is.
Key terms
- Multi-agent social simulation
- A method that reproduces, inside a computer, how multiple entities such as people and robots interact, in order to study the behavior of the whole
- Large language model
- Artificial intelligence that learns how words fit together from a large amount of text, enabling it to read and write sentences
- Werewolf AI (AIWolf)
- A research framework in which artificial intelligence plays the conversation-based game "Werewolf," where players try to identify each other's hidden roles
NewsLab news
A doctoral student received the Money Forward, Inc. Award at the Young Researchers' Symposium on Natural Language Processing (YANS)
A master's student received the YANS Committee Special Award at the Young Researchers' Symposium on Natural Language Processing
A doctoral student received the Best Paper Award of the 40th Anniversary Commemorative Paper Award from the Japanese Society for Artificial Intelligence
A master's student and a faculty member received the FY2025 Research Meeting Excellence Award from the Japanese Society for Artificial Intelligence
A master's student received the Young Researcher Encouragement Award at the 32nd Annual Meeting of the Association for Natural Language Processing
ResearchResearch themes
The lab pursues research centered on an engineering question: the social application of artificial intelligence technology. With multi-agent social simulation and natural language processing as its two pillars, it works on topics such as transportation systems, automated warehouses, finance and economics, and medical texts.
*Illustrative imageMulti-Agent Social Simulation
Taking transportation systems and automated warehouses as subjects, the lab uses artificial intelligence and agent-based simulation to explore optimization and sustainable development methods that allow large systems and societies to run efficiently.
*Illustrative imageBig Data Analysis
As a foundation for multi-agent social simulation, the lab develops methods for statistically analyzing the movements of the people and objects that make up society.
*Illustrative imageCausal Knowledge and Large Language Models
The lab combines large language models specialized for particular domains with reasoning based on causal knowledge extracted from them, exploring ways to build practical and accurate artificial intelligence systems.
*Illustrative imageGames and AI
Taking Werewolf AI as a subject, the lab explores mechanisms for making human-like decisions from uncertain and inaccurate information.
MembersFaculty
The members of the Intelligent Software Lab consist of faculty members, a secretary, and students in the doctoral, master's, and bachelor's programs.As of 2026
- ProfessorItsuki Noda
- Associate ProfessorHiroki Sakaji
- Project Assistant ProfessorYukiko Ogura
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Yujing Line expressway and Provincial Highway at midnight” Guanting Chen / CC BY-SA 4.0 (cropped)
- Multi-Agent Social Simulation: “Automated Storage and Retrieval System” QmcBeQ3G7DZCmY84uPgT / CC BY 4.0 (cropped)
- Big Data Analysis: “Datacenter Server Racks ( )” Carl Lender from Sunrise, USA / CC BY 2.0 (cropped)
- Causal Knowledge and Large Language Models: “Newspaper Stack ( )” Babak Farrokhi from Tehran, IRAN / CC BY 2.0 (cropped)
- Games and AI: “Table game of cards birds eye view (cropped)” Esteffect / Public domain (cropped)
- Related lab (調和系
工学研究室): “Snow removal in Sapporo ( )” MIKI Yoshihito / CC BY 2.0 (cropped) - Related lab (情報知識ネットワーク研究室): “Code on computer monitor (Unsplash)” Markus Spiske markusspiske / CC0 (cropped)
- Related lab (メディアダイナミクス研究室): “Aperture grille closeup” Selçuk Oral (drumex) / CC BY-SA 3.0 (cropped)
- Related lab (言語メディア学研究室): “Rosetta Stone” Hans Hillewaert / CC BY-SA 4.0 (cropped)
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