Mathematical frameworks for the analysis of norms

Abstract

Research into society's informal rules of conduct, or norms, has recently experienced a surge, extending across multiple academic disciplines. Despite this growth, the theoretical modeling of norms often remains siloed within specific paradigms, as different disciplines tend to favor certain frameworks over others, thereby hindering the spread of innovative ideas. This article breaks through disciplinary barriers to explore recent advancements in the mathematical study of norms. It specifically focuses on cutting-edge theoretical research, structuring the discussion around four general frameworks: game theory, evolutionary game theory, agent-based modeling, and multi-agent reinforcement learning.