{"slug": "llm-powered-reasoning-in-agent-based-modeling", "title": "LLM-powered reasoning in agent-based modeling", "summary": "Researchers introduced HALE, a hybrid agent-based and language-driven epidemic modeling framework that uses large language models to predict human decision-making in simulations, demonstrated by modeling COVID-19 in Salt Lake County, UT.", "body_md": "# Computer Science > Artificial Intelligence\n\n[Submitted on 7 Jul 2026]\n\n# Title:LLM-powered reasoning in agent-based modeling\n\n[View PDF](/pdf/2607.06757)\n\n[HTML (experimental)](https://arxiv.org/html/2607.06757v1)\n\nAbstract:Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making. However, ABMs have traditionally relied on static prior, which prevents the models from adapting to real-time changes. Our research provides a novel approach to addressing this information gap. Large language models (LLMs) offer new opportunities to predict human decision-making. Here, we introduce a scalable Hybrid Agent-based and Language-driven Epidemic (HALE) modeling framework that leverages LLMs to predict human decision-making in an ABM simulation. As a proof-of-concept, we use HALE to simulate COVID-19 and its effects in Salt Lake County, UT.\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/llm-powered-reasoning-in-agent-based-modeling", "canonical_source": "https://arxiv.org/abs/2607.06757", "published_at": "2026-07-09 04:00:00+00:00", "updated_at": "2026-07-09 04:16:52.899790+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-research"], "entities": ["HALE", "Salt Lake County"], "alternates": {"html": "https://wpnews.pro/news/llm-powered-reasoning-in-agent-based-modeling", "markdown": "https://wpnews.pro/news/llm-powered-reasoning-in-agent-based-modeling.md", "text": "https://wpnews.pro/news/llm-powered-reasoning-in-agent-based-modeling.txt", "jsonld": "https://wpnews.pro/news/llm-powered-reasoning-in-agent-based-modeling.jsonld"}}