Advancing Computational Social Science, Multi-Agent Systems, and AI-Driven Decision Modeling through International Research Collaboration.
Background & Purpose
With rapid advancements in Artificial Intelligence and Computational Science, interdisciplinary research leveraging mathematical models, statistical physics, and data-driven methodologies has become essential. These innovative approaches enable researchers to analyze complex social phenomena—including social dilemmas, cooperative behavior, social learning, and evolving social norms.
By bringing together researchers from Shizuoka University (Japan) and Pukyong National University (Korea), this symposium aims to share recent findings in computational social science and scientific computing. It serves as a foundational platform to foster sustained international collaboration, joint research, and academic exchange.
Key Themes & Focus Areas
Mathematical modeling of multi-agent cooperative behavior and practical applications leveraging Large Language Models (LLMs).
Case studies applying Bayesian approaches to social learning and demand forecasting models in open dynamic systems.
Cultural characteristics of social norms, personality-driven cooperation, and mitigating opinion polarization in social networks.
Schedule & Presentations
Pukyong National University (PKNU), Daeyeon Campus
45, Yongso-ro, Nam-gu, Busan, Republic of Korea
Mirae Hall (미래관) is located near the main entrance of Pukyong National University Daeyeon Campus. The CEO Hall is situated on the 2nd floor.
Department of Scientific Computing, Pukyong National University
Hosts & Supporters
Pukyong National University