mlsanityData to 7 Oct 2026

CoRenew: A large language model agent-based policy simulation platform for multifamily residential redevelopment

arXiv 2607.25447 ↗First posted 28 Jul 2026cs.MAcited by 0

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

The difficulty of collective action remains a central challenge in the design of policies for multifamily residential redevelopment. Stakeholders continually adjust their decisions in response to evolving negotiation contexts and the reactions of others, meaning that when a policy intervenes and which stakeholders it targets can substantially reshape collective outcomes. Assessing these adaptive responses ex ante remains difficult because existing simulation models often rely on predefined behavioral rules. Here, we present CoRenew, an open-source platform that uses LLM-based agents to simulate negotiations among multiple stakeholders and evaluate the effects of alternative policy combinations. Integrating open source geographic and demographic data, the platform can generate synthetic residents, simulate negotiation dynamics under alternative policy settings and compares policy performance across competing objectives. It supports both numerical and semantic policy inputs and includes built-in tools for visualization and result export. We validate its behavioral realism against survey responses from 324 residents and a nine-month observed negotiation process from a real redevelopment case. With its modular and adaptable architecture, CoRenew can be used to assess policies across different institutional and cultural contexts.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 7 of its 52 references that are in the map. First posted on arXiv 28 Jul 2026.

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7 of 52 references.

Closest ancestors · 2

Same direction, newest first

  1. 2026PolicySim: An LLM-Based Agent Social Simulation Sandbox for Proactive Policy Optimization20 Mar
  2. 2024Simulating Multi-Stakeholder Decision-Making with Generative Agents in Urban Planning17 Feb

Other references · 5

  1. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
  2. 2023Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectivescited by 253
  3. 2023Generative Language Models Exhibit Social Identity Biasescited by 107
  4. 2023Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiationcited by 94
  5. 2025EconGym: A Scalable AI Testbed with Diverse Economic Taskscited by 2

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