PROJECT SUMMARY

GenAISim: Simulation in the Loop for Multi-Stakeholder Interactions with Generative Agents
Focus Areas: News & Media, Mobilities, Social Services, Health
Status: Active
Traditional decision-making processes often struggle to adapt to the dynamic and multifaceted nature of the modern world. This research addresses a higher-level profound need for advanced automated decision-making tools that can address complex, context-rich challenges in society.
This project will investigate a hybrid decision-making system, leveraging cooperative knowledge from multiple stakeholders through socio-technical observations, and knowledge priors in Large Language Models (LLMs) and open datasets.
It will develop GenAISim, a novel suite of generative and data driven simulations, useful for depicting current and future urban scenarios, including in mobility, urban policymaking, and health domains. Through a multidisciplinary sociotechnical framework of investigation, this project will establish a new simulation in the loop paradigm.
PROJECT OBJECTIVES
- Explore LLM agent-based synthetic data generation techniques to simulate and augment human behaviours in diverse contexts;
- Develop a robust framework for hypothesis testing of real-world observations and relationships, while avoiding spurious correlations;
- Investigate diverse stakeholder settings, often with nonoverlapping and potentially conflicting objectives, priorities, constraints, incentives and pain points; and
- Explore questions around hybrid decision making – if an LLM agent is substituting for a decision maker in contexts.
MORE INFORMATION
RESEARCHERS























PARTNERS

Bendigo
Hospital

Halmstad
University

University of
Amsterdam
COLLABORATORS

Gradient Institute
