One of the most challenging problems in network analysis is the identification of the community structure, with applications in various fields such as politics, economics, biology, physics, etc.. Among the most important effects of the existence of the community structure in networks is the effect on information diffusion with immediate applications in economics and social sciences. Our project aims to design a new tool for identifying both the community structure and the appropriate information diffusion model in an integrated adaptive manner by using computational intelligence methods and equilibria concepts from game theory.
The originality of the approach consists in combining game theory tools (game models and equilibria concepts) with highly scalable nature inspired search and optimization methods in order to address both the community detection and information diffusion problems.Meet us!
Main interests: game theory, evolutionary algorithms
Main interests: computational game theory, evolutionary algorithms
Main interests: evolutionary optimization, game theory, web services composition
Main interests: artificial intelligence, game theory, evolutionary computation