Research
At APES Lab, we develop computational frameworks that enable researchers and policymakers to explore complex socioeconomic systems through multi-agent simulation. Our work bridges theoretical economics with practical policy analysis.
SANE v0.5
Simulative Agent-based Normative Environment
SANE is our open-source multi-agent simulation framework designed specifically for policy and economic research. Unlike traditional agent-based models, SANE leverages large language models to create agents with nuanced decision-making capabilities, enabling realistic simulation of human behavior at scale.
- Scale to millions of heterogeneous agents
- LLM-powered behavioral modeling for realistic decisions
- Modular architecture for custom policy environments
- Validated against historical economic data
SANE v0.5 Architecture
Methodology
Our research methodology combines insights from computational economics, behavioral science, and machine learning to create simulations that capture the complexity of real-world systems.
Agent Design
Each agent is endowed with beliefs, preferences, and decision-making capabilities powered by fine-tuned language models. Agents respond to incentives, learn from experience, and adapt to changing environments.
Environment Specification
We construct detailed institutional environments that capture market structures, regulatory frameworks, and information flows. These environments are calibrated to match real-world economies.
Validation & Analysis
Simulations are validated against historical data and stylized facts. We use ensemble methods and sensitivity analysis to quantify uncertainty and identify robust policy conclusions.
Foundational Research
The academic foundations our work builds upon—pioneering research in agent-based modeling, computational economics, and LLM-driven simulation
Agent-Based Computational Economics: Growing Economies From the Bottom Up
Tesfatsion, L.
Artificial Life • 2002
Growing Artificial Societies: Social Science from the Bottom Up
Epstein, J.M. & Axtell, R.
MIT Press • 1996
Agent-Based Models in Economics: A Toolkit for Policy Analysis
Dawid, H. & Delli Gatti, D.
Handbook of Computational Economics • 2018
The Economy as an Evolving Complex System II
Arthur, W.B., Durlauf, S.N., & Lane, D.A.
Santa Fe Institute Studies • 1997
Generative Agents: Interactive Simulacra of Human Behavior
Park, J.S., O'Brien, J.C., Cai, C.J., et al.
UIST 2023 • 2023
Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies
Argyle, L.P., Busby, E.C., Fulda, N., et al.
PNAS • 2023
Data & Models
We are committed to open science. Access our datasets, trained models, and replication materials for published research.