用智能代理系统让家庭饮食既省钱又营养均衡。
FinAgent: An Agentic AI Framework Integrating Personal Finance and Nutrition Planning
- 分模块的智能代理协同规划，实时响应价格波动。
- 成本降低12%-18%，营养达标率超95%。
- 适合关注健康饮食与家庭预算者使用。
中等收入家庭面临预算有限与食品价格波动的双重挑战。本文提出一种具备价格感知能力的智能体框架（FinAgent），将个人财务管理与膳食优化结合。基于家庭收入、固定支出、健康状况及实时食品价格，系统生成营养充足且价格合理的膳食计划，并能自动适应市场变化。该框架采用模块化多智能体架构，包含预算管理、营养分析、价格监控和健康个性化等专用智能体，共享知识库并通过替换图确保营养质量的同时最小化成本。以沙特代表性家庭为例的模拟实验显示，相比静态周菜单，成本降低12%-18%，营养达标率超过95%，在价格波动20%-30%时仍保持高效率。研究结果表明，该框架可实现本地化饮食的经济性与营养性的统一，为落实零饥饿与良好健康可持续发展目标提供可行路径。
原文摘要 · Abstract (English)
The issue of limited household budgets and nutritional demands continues to be a challenge especially in the middle-income environment where food prices fluctuate. This paper introduces a price aware agentic AI system, which combines personal finance management with diet optimization. With household income and fixed expenditures, medical and well-being status, as well as real-time food costs, the system creates nutritionally sufficient meals plans at comparatively reasonable prices that automatically adjust to market changes. The framework is implemented in a modular multi-agent architecture, which has specific agents (budgeting, nutrition, price monitoring, and health personalization). These agents share the knowledge base and use the substitution graph to ensure that the nutritional quality is maintained at a minimum cost. Simulations with a representative Saudi household case study show a steady 12-18\% reduction in costs relative to a static weekly menu, nutrient adequacy of over 95\% and high performance with price changes of 20-30%. The findings indicate that the framework can locally combine affordability with nutritional adequacy and provide a viable avenue of capacity-building towards sustainable and fair diet planning in line with Sustainable Development Goals on Zero Hunger and Good Health.
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