SimViews: An Interactive Multi-Agent System Simulating Visitor-to-Visitor Conversational Patterns to Present Diverse Perspectives of Artifacts in Virtual Museums
Mingyang Su, Chao Liu, Jingling Zhang, WU Shuang, Mingming Fan

TL;DR
SimViews is an interactive multi-agent system that uses AI-powered virtual visitors to simulate conversations, presenting diverse perspectives on artifacts in virtual museums and improving visitor engagement and understanding.
Contribution
This paper introduces SimViews, a novel multi-agent system that simulates visitor interactions to effectively showcase multiple viewpoints in virtual museums.
Findings
SimViews enhances understanding of diverse perspectives.
Participants showed increased engagement with SimViews.
The system successfully simulates visitor conversations.
Abstract
Offering diverse perspectives on a museum artifact can deepen visitors' understanding and help avoid the cognitive limitations of a single narrative, ultimately enhancing their overall experience. Physical museums promote diversity through visitor interactions. However, it remains a challenge to present multiple voices appropriately while attracting and sustaining a visitor's attention in the virtual museum. Inspired by recent studies that show the effectiveness of LLM-powered multi-agents in presenting different opinions about an event, we propose SimViews, an interactive multi-agent system that simulates visitor-to-visitor conversational patterns to promote the presentation of diverse perspectives. The system employs LLM-powered multi-agents that simulate virtual visitors with different professional identities, providing diverse interpretations of artifacts. Additionally, we…
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