End-to-End Python framework implementing bias-adjusted LLM agents for human-like decision-making in economic games (Kitadai et al., 2025). Features persona-conditioned agent populations using Econographics data, multi-provider API integration, and Wasserstein distance validation against empirical benchmarks.
python data-science simulation scientific-computing game-theory agent-based-modeling human-behavior computational-social-science experimental-design behavioral-economics ultimatum-game economic-modeling bias-mitigation digital-twins reproducible-researc large-language-models llm-api statistical-validation ecision-making persona-conditioning
-
Updated
Aug 29, 2025 - Jupyter Notebook