Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
| Date | Stars |
|---|---|
| 2026-07-31 | 297 |
| 2026-08-06 | 298 |
| 2026-08-18 | 299 |
| 2026-08-22 | 301 |
| 2026-09-12 | 302 |
| 2026-09-16 | 302 |
| 2026-09-18 | 303 |
| 2026-10-02 | 302 |
| 2026-10-11 | 303 |
| 2026-10-20 | 304 |
| 2026-10-23 | 305 |
| 2026-11-04 | 305 |
Today
— stars today
This week
— stars this week
This month
+3 stars this month
Momentum
0.0
growth rate 0.00%/day
# Large language model (LLM) agent-based modeling and simulation
A summary of works on LLM empowered agent-based modeling and simulation.
Our survey **Large language models empowered agent-based modeling and simulation: a survey and perspectives** is published in Humanities and Social Sciences Communications.
Please refer to the paper: [link](https://www.nature.com/articles/s41599-024-03611-3)
Please cite our survey paper if you find our work helpful.
```
@article{gao2024large,
title={Large language models empowered agent-based modeling and simulation: A survey and perspectives},
author={Gao, Chen and Lan, Xiaochong and Li, Nian and Yuan, Yuan and Ding, Jingtao and Zhou, Zhilun and Xu, Fengli and Li, Yong},
journal={Humanities and Social Sciences Communications},
volume={11},
number={1},
pages={1--24},
year={2024},
publisher={Palgrave}
}
```
# Table of Contents
- [Challenges and approaches of LLM for ABS](#Challenges-and-approaches-of-LLM-for-ABS)
- [Environment Construction and Interface](#Environment-Construction-and-Interface)
- [Human Alignment and Personalization](#Human-Alignment-and-Personalization)
- [How to simulate actions](#How-to-simulate-actions)
- [Evaluation of LLM agents](#Evaluation-of-LLM-agents)
- [Recent advances of LLM for ABS](#Recent-advances-of-LLM-for-ABS)
- [Social Domain I: Social Sciences](#Social-Domain-I-Social-Sciences)
- [Social Network Dynamics](#Social-Network-Dynamics)
- [Cooperation](#Cooperation)
- [Individual Social Behavior](#Individual-Social-Behavior)
- [Social Domain II: Economic System](#Social-Domain-II-Economic-System)
- [Individual Economic Behavior](#Individual-Economic-Behavior)
- [Interactive Economic Behavior](#Interactive-Economic-Behavior)
- [Economic System](#Economic-System)
- [Physical Domain](#Physical-Domain)
- [Cyber Domain](#Cyber-Domain)
- [Hybrid Domain](#Hybrid-Domain)
## Challenges and approaches of LLM for ABS
### Environment Construction and Interface
| **Name** | **Paper** | **Venue** | **Code** |
| --- | --- | --- | --- |
| ChatDev | [Qian, C., Cong, X., Yang, C., Chen, W., Su, Y., Xu, J., ... & Sun, M. (2023). Communicative agents for software development. arXiv preprint arXiv:2307.07924.](https://openreview.net/pdf?id=yW0AZ5wPji) | arxiv | [Python](https://github.com/OpenBMB/ChatDev) |
| RecAgent | [Wang, L., Zhang, J., Chen, X., Lin, Y., Song, R., Zhao, W. X., & Wen, J. R. (2023). Recagent: A novel simulation paradigm for recommender systems. arXiv preprint arXiv:2306.02552.](https://arxiv.org/pdf/2306.02552) | arxiv | |
| Generative Agents| [Park, J. S., O'Brien, J., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023, October). Generative agents: Interactive simulacra of human behavior. In Proceedings of the 36th annual acm symposium on user interface software and technology (pp. 1-22).](https://dl.acm.org/doi/pdf/10.1145/3586183.3606763) | UIST|[Python](https://github.com/joonspk-research/generative_agents) |
|EconAgent| [Li, N., Gao, C., Li, Y., & Liao, Q. (2023). Large language model-empowered agents for simulating macroeconomic activities. arXiv preprint arXiv:2310.10436.](https://arxiv.org/pdf/2310.10436) |ACL|[Python](https://github.com/tsinghua-fib-lab/ACL24-EconAgents)|
|WebAgent| [Gur, I., Furuta, H., Huang, A. V., Safdari, M., Matsuo, Y., Eck, D., & Faust, A. A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis. In The Twelfth International Conference on Learning Representations.](https://arxiv.org/pdf/2307.12856) |ICLR ||
|UGI| [Xu, F., Zhang, J., Gao, C., Feng, J., & Li, Y. (2023). Urban generative intelligence (ugi): A foundational platform for agents in embodied city environment. arXiv preprint arXiv:2312.11813.](https://arxiv.org/pdf/2312.11813) |Arxiv||
|GITM| [Zhu, X., Chen, Y., Tian, H., Tao, C., Su, W., Yang, C., ... & Dai, J. (2023). Ghost in the minecraft: Generally capable agents forExcerpt of 29,984 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c0ab3155b5ebe735, llm:Repository name: 'LLM-Agent-Based-Modeling-and-Simulation' suggests use of large language models (LLM) for agent-based modeling and simulation.
matched fp:c0ab3155b5ebe735, llm:Repository name: 'LLM-Agent-Based-Modeling-and-Simulation' suggests use of large language models (LLM) for agent-based modeling and simulation.
matched fp:c0ab3155b5ebe735, llm:Repository name: 'LLM-Agent-Based-Modeling-and-Simulation' suggests use of large language models (LLM) for agent-based modeling and simulation.