Research Summary: LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems

The research introduces LiveSim, a novel framework leveraging Large Language Models (LLMs) to simulate dynamic user behavior within multi-agent live-stream ecosystems. Unlike traditional methods relying on static user profiles, LiveSim progressively refines user behavioral hypotheses based on real-time, trajectory-grounded interactions. This approach allows for the identification and integration of environmental shaping effects that continuously alter user behavior, enhancing the realism and adaptability of simulations.

Why it matters

This development is strategically significant as it offers a more sophisticated method for understanding and predicting complex user behavior in dynamic digital environments. The ability to simulate how environments shape user actions provides organizations with critical insights for adaptive strategy development, content optimization, and platform design, leading to more resilient and responsive operational models.

Key insights

• Existing user behavior simulation approaches often fall short in socially intensive environments due to their reliance on static user profiles.
• LiveSim is an LLM-based framework designed for live-stream ecosystem simulation.
• It represents users as editable behavioral hypotheses that are refined through trajectory-grounded interactions.
• Discrepancies between simulated and observed trajectories are used to reveal and integrate environmental shaping effects.
• These environmental signals are extracted as transferable components, suggesting broader applicability beyond live-stream contexts.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.26849