Integrating Agent Learning with System Dynamics in an Agent-Based Model of Economic Development

This paper(1) integrates evolutionary game in an agent-based model, with application in economic development. It answers the question of how does individual agency impact a country's development trajectory, at both the micro and macro level. The model simulates how individuals act, react, and interact in different societies through learning process. It demonstrates how macro structures provide political, social and economic environments that constrain or incentivize micro level human behavior, while the feedback loop of individual agent actions on structure paves the way for explaining and predicting political, economic and social explanations across all human scales of behavior and levels of analysis. Simulation result is compared against real world data, suggesting policy implications for society at different stages of development.