Social/Cultural Modeling Through Computational and Evolutionary Game Theoretic Models

My thesis work on social/cultural modeling focused on developing computational and evolutionary game theoretic models of human behavior, decision making, culture, and their evolution. I think it’s a fascinating topic, and in this post I just wanted to give a brief high-level intro of what this type of work is about.

Example of the proportions of different behaviors in a population over time and under evolutionary pressures.

Evolutionary computation techniques—and in particular, evolutionary game theory—can be quite useful in providing an understanding of the dynamics of human behavior and its evolution in social systems. Behaviors in human social systems are subject to evolutionary selection pressures through cultural adaptation processes such as social learning (e.g. payoff-biased imitation or learning). In this context the fitness of behaviors depends on the abundance of other behaviors in the population, the interaction structure or social network of the population, and other contextual factors that affect the nature of interactions and their outcomes.

Evolutionary game theoretic models can enhance our understanding of complex human social worlds by helping to discover relationships between factors in the environment and evolutionary behavioral outcomes and dynamics. Specific phenomena I have explored include the evolution of third-party punishment behavior and cross-cultural differences in punishment behavior norms. This research was strongly grounded in social science data and conducted in close collaboration with social scientists. By providing explanatory models of the emergence of different observed behaviors, the evolutionary models we developed and studied established support for causal relationships among socio-cultural factors and behavioral phenomena that are difficult or impossible to test or infer empirically. These types of models can also be used to test hypothetical scenarios and create predictive tools that can be of use in a variety of application domains.

A good intro on evolutionary game theory specifically, although framed mostly in the biological context, can also be found here: