Summary
2023
Session Number:A4L-4
Session:
Number:A4L-43
Social Network Formation Model Considering Penalties Against Social Rationality Reduction
Imai Tetsuo,
pp.181-184
Publication Date:2023-09-21
Online ISSN:2188-5079
Summary:
Author and co-researcher have proposed the dynamic network formation game model for modeling complex networks. This model represents dynamical network formation process derived by many distributed decision making by selfinterest agents. In this model, varied players' payoff function leads players' strategy to change, thus different outcome networks are generated. Therefore if the payoff function can be controlled, the formed network structures can be controlled in some degree. In the event of pandemics of infectious diseases such as COVID-19, it is important to change the structure of the social and infection transmission network. In this article, I examine a method for balancing individual and social rationality in social network formation using the dynamic network formation game model. a payoff function reflecting individual and social rationality is introduced, and the characteristics of generated network structures are investigated through computer simulation. The results showed that the resulting networks tended to be unnatural networks as social networks, but by introduced payoff function, structures with high resistance to the spread of infectious diseases were obtained.