Keynote Speakers

Dr. Yasushi Kambayashi

Professor, Department of Informatics and Data Science, Sanyo-Onoda City University

Keynote Speech: 

Multi-Agent Base Evacuation Support System Using MANET

Short Abstract: We propose an evacuation support system that provides evacuation routes in case of disasters. When communication base stations break down due to disasters such as an earthquake, it becomes difficult for people to use their smartphones based on the Internet. When the communication infrastructure is paralyzed, people have great difficulty collecting information about the conditions of transportation systems and the states of family and friends using smartphones. Our proposed system addresses this problem by using multiple kinds of mobile agents in addition to static agents on smartphones that use a mobile ad hoc network (MANET). The proposed system collects information with mobile agents and diffuses information via mobile agents so that the system is able to provide an optimized evacuation route for each user in a dynamically changing environment. For example, when a tsunami or a flood tide occurs, low elevations may be under water. Therefore, the evacuation support system must help people to move to safer places by selecting higher elevation routes when warranted by the situation. This smartphone-based system may work in urban area, but may not work in sparsely populated areas, such as mountainous regions, evacuees may not have access to information to the situation due to the paralyzed communication infrastructure. In order to address this problem, we are now proposing another evacuation support system after disasters using Unmanned Aerial Vehicles (UAVs). We have two types of UAVs for this system. One type of UAVs surveys the road conditions and collects information about affected individuals, while another type of UAVs guides the evacuees based on the collected information by the former UAVs. We are developing a simulator for the feasibility study of this system.

Dr. Filippo Sciarrone

Associate Professor, Universitas Mercatorum – Department of Science and Technology, Rome, Italy

Keynote Speech: 

Generative AI and Education: a winning combination?

Short Abstract: One of the key strengths of Large Language Models (LLMs) and generative AI is their ability to understand human language with remarkable depth and nuance. This enables them to reason logically, plan effectively, and carry out complex tasks. As a result, there’s growing confidence that, in the age of AI, anyone can learn to program—simply by using natural language. For educators, this means new opportunities to collaborate with Generative AI in developing lesson plans and educational materials. By learning how to design and deploy AI agents, teachers can personalize instruction based on diverse student needs, guided by established learning theories and adaptive teaching strategies. My talk addresses the relationship between generative AI and education. In particular, I will show the state of the art regarding the application of conversational agents, or intelligent chatbots, as learning aids for students, including students with learning disabilities. Intelligent chatbots, based on Generative AI,  can act as extensions of the human teacher, transcending physical boundaries to provide continuous, accessible learning experiences. In this presentation, I explore the conceptual foundations and design principles behind pedagogical AI agents. I will also give live demonstrations showing how these agents can operate, showing web-based systems acting for dyslexic students.