对于近视特征的行为分析
Yonatan Mintz1, Anil Aswani2, Philip Kaminsky2
1Department of Industrial and Systems Engineering, University of Wisconsin - Madison, 53706.
概括
本研究引入了一种行为分析方法,以优化在预算限制范围内优化代理激励措施. 该方法有效地降低了高达60%的项目成本,同时保持了有效性.
科学领域:
- 多代理系统是多代理系统.
- 行为经济学是一种行为经济学.
- 优化优化 优化优化
背景情况:
- 多代理系统中的协调员面临预算限制和未知的代理实用功能.
- 代理人的决定取决于未知的先前状态,输入和参数.
研究的目的:
- 开发一种行为分析框架,以优化代理激励.
- 为了应对预算限制和未知的代理公用事业的协调员挑战.
主要方法:
- 建模代理人的决策过程.
- 估计使用数据预测未来决策的代理模型参数.
- 通过使用主整数程序的分解方案优化激励措施.
主要成果:
- 拟议的框架在收集新信息时以适应性优化激励措施.
- 计算的激励被证明是异常最优的.
- 一个个性化减肥计划的模拟显示,在维持有效性的情况下,成本降低了高达60%.
结论:
- 行为分析方法为受约束的多代理系统中激励优化提供了有效的解决方案.
- 与适应式启发学相比,这种框架显著降低了成本.
- 该方法通过在个性化健康计划中成功应用得到了验证.
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