用不同角色协作生成创意，提升想法多样性与深度。
Persona-based Multi-Agent Collaboration for Brainstorming
- 为每个智能体分配特定角色（如医生、工程师），引导创意方向。
- 角色搭配和协作模式影响创意的广度与深度，最佳组合可覆盖跨领域观点。
- 适合需要多角度创新的场景，如产品设计、战略规划。
我们证明了基于角色的多智能体头脑风暴在多样化主题和专业领域创意生成中的重要性。先前研究显示，通用多智能体协作比单个智能体推理更优。本文提出并开发了一种基于角色的智能体选择框架，表明角色领域筛选能提升头脑风暴效果。通过多种实验设置，评估不同角色组合（如医生对虚拟现实工程师）及智能体间交互模式（独立、协同、先独立后协同）下的创意产出。结果表明：(1) 角色选择决定创意领域分布；(2) 协作模式影响创意多样性；(3) 多智能体角色驱动的头脑风暴可实现创意深度与跨领域覆盖。
原文摘要 · Abstract (English)
We demonstrate the importance of persona-based multi-agents brainstorming for both diverse topics and subject matter ideation. Prior work has shown that generalized multi-agent collaboration often provides better reasoning than a single agent alone. In this paper, we propose and develop a framework for persona-based agent selection, showing how persona domain curation can improve brainstorming outcomes. Using multiple experimental setups, we evaluate brainstorming outputs across different persona pairings (e.g., Doctor vs VR Engineer) and A2A (agent-to-agent) dynamics (separate, together, separate-then-together). Our results show that (1) persona choice shapes idea domains, (2) collaboration mode shifts diversity of idea generation, and (3) multi-agent persona-driven brainstorming produces idea depth and cross-domain coverage.
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