用多智能体系统为园艺提供有温度的个性化指导。
CultivAgents: Cultivating Relationship-Centered Multi-Agent Systems for Personalized Gardening

- 三个专用智能体协同:经验、环境与民族植物学视角
- 用户信心、动机与信任均显著提升,最高升0.8分
- 适合关注食物主权与文化传承的社区园艺者
园艺对身心健康、文化延续和食物自主至关重要,但现有数字工具常提供泛化建议,忽略园丁技能、本地生态、季节与文化背景。我们提出CultivAgents,一种以关系为中心的多智能体系统,支持个性化、社会文化扎根的园艺辅助。该系统基于关怀伦理,协调三个专精智能体:经验智能体根据用户技能调整建议,环境智能体结合本地与季节条件,民族植物学智能体连接植物与文化知识历史。通过包含3位领域专家、7位人机交互研究者和5位社区园丁的三阶段混合方法研究,分析专家反馈、前后测问卷及参与式设计活动。结果表明,CultivAgents帮助园丁将兴趣转化为具体行动:社区园丁自评信心从3.00升至3.60,动机从4.00升至4.40,对AI建议的信任从3.20升至4.00。参与者重视本地生态指引与多视角互补,但也指出文化细节、生态嵌入与智能体协作仍存局限。本研究推动关系导向型AI发展,为支持食物主权、社区韧性与文化保存的多智能体系统提供设计启示。
原文摘要 · Abstract (English)
Gardening is critical to support well-being, cultural continuity, and food autonomy, yet existing digital tools often provide generic advice that overlooks gardeners' skills, local ecologies, seasons, and cultural contexts. We introduce CultivAgents, a relationship-centered multi-agent system for personalized, socio-culturally grounded gardening support. Grounded in ethics of care, CultivAgents coordinates multiple specialized agents: an Experience Agent that adapts guidance to users' skill levels, an Environmental Agent that grounds advice in local and seasonal conditions, and an Ethnobotanical Agent that connects plants to cultural knowledge and histories. We evaluated CultivAgents through a three-phase mixed-methods study with domain experts (n=3), HCI researchers (n=7), and community gardeners (n=5), analyzing expert feedback, pre/post surveys, and participatory design activities. Results suggest that CultivAgents helped gardeners translate interest into situated action: community gardeners reported increased confidence (3.00 to 3.60), motivation (4.00 to 4.40), and trust in acting on AI advice (3.20 to 4.00). Participants valued hyperlocal ecological guidance and complementary agent perspectives, while also identifying limits in cultural specificity, ecological grounding, and agent coordination. The work advances relationship-centered AI, offering design implications for multi-agent systems that support food sovereignty, community resilience, and cultural preservation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。