Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
August 15, 2025Emerging MediaOpen Access

Agentic AI for Sustainable Development: Leveraging Large Language Model-Enhanced Agent-Based Modeling for Complex Policy Strategies

View Full Paper
Ask AI
Bookmark
Share

Authors

JLJ LiuCCChu ChuYZYilin Zhao

Discussion

Loading...

Member takes

Overview

This analysis demonstrates how agent-based modeling and large language models can enhance simulations focused on sustainable development goals, suggesting new avenues for policy experimentation.

Key Points

  • Integrating agent-based modeling with large language models improves simulations for sustainable development goals, enhancing their cultural relevance.
  • Emergent behaviors in complex systems can be simulated more realistically by using adaptive, context-aware AI agents trained with large language models.
  • The approach combines technology to advance policy experimentation while addressing ethical and technical challenges, including reasoning limitations and accountability.
  • Proposes interdisciplinary research and governance strategies to ensure responsible use of AI in policymaking, matching innovation with oversight.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/68a365600a429f797332b69chttps://doi.org/10.1177/27523543251365678
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1LLM-Augmented Agent-Based Modelling for Social Simulations: Challenges and Opportunities2024 · 4 citations
  2. 2Cooperate or Collapse: Emergence of Sustainability Behaviors in a Society of LLM Agents2024 · 4 citations
  3. 3CERN for AI: a theoretical framework for autonomous simulation-based artificial intelligence testing and alignment2024 · 20 citations
  4. 4The Intertwined Fates of Human and Artificial Agents: Navigating the Evolving Landscape of LLM-Driven Agents2025
  5. 5Intelligent Digital Agents in the Era of Large Language Models2024