Optimal Sequential Allocation in Dynamic Environments

动态环境中的最优顺序分配

• 批准号: 0906424
• 负责人: Philippe Rigollet
• 金额: $ 11万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0906424&HistoricalAwards=false
• 关键词: Optimal; Sequential; Allocation; Dynamic; Environments

Bandit problems have been studied in many different contexts and variations. The vast majority of work focuses on a static environment, in which, at each time, the probability distribution of the reward yielded by each action remains unchanged. This static model may clearly fail to produce decision strategies that are optimal in a dynamically changing environment. Despite their sounding relevance in practical applications, such environments have received sporadic attention in the statistical community so far. The contribution of the proposed research to the current state of knowledge will consist in proposing models for new dynamic environments that are motivated by a significant class of applications, designing policies that adapt to dynamic environments, analyzing the performance of these policies and assessing optimality from a finite time (non asymptotic) point of view.Sequential allocation in dynamic environments is a problem that arises at the intersection of nonparametric statistics, machine learning and operations research. This project involves techniques from these fields and points out fundamental bridges between the extant results to form a more unified theory of the subject. This theory will then serve as a basis for producing computationally efficient allocation policies with potential applications in clinical trials, drug discovery and real time web page content optimization.

已在许多不同的情况和变化中研究了匪徒问题。绝大多数工作都集中在静态环境上，在这种环境中，每种动作产生的奖励的概率分布保持不变。这种静态模型可能显然无法制定在动态变化的环境中最佳的决策策略。尽管在实际应用中听起来很重要，但到目前为止，这种环境在统计社区中受到了零星的关注。拟议的研究对当前知识状态的贡献将包括针对新的动态环境的模型，这些模型是由一系列应用程序所激发的，这些应用程序是针对适应动态环境的设计策略，分析这些策略的性能并评估有限时间（非违反时间（非违反）的分配和动态分配的问题）的效果。 研究。该项目涉及这些领域的技术，并指出现存结果之间的基本桥梁，形成了对主题的更统一的理论。然后，该理论将作为在临床试验，药物发现和实时网页内容优化中使用潜在应用来制定计算有效分配策略的基础。