This paper introduces AI Tour Meeting, a framework in which multiple LLM-based agents with distinct personas discuss and construct group travel itineraries. Agents negotiate constraints and preferences through natural-language interaction. The framework provides interfaces for configuring personas, discussion workflows, monitoring, and LLM deployment. Its stated primary use case is simulation and analysis of multi-agent behavior during tour planning. The abstract reports system validation and several analytical results, but does not provide quantitative metrics, datasets, model configurations, or comparison baselines.
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