Workshop: A Conversation Between AI and OR on Sequential Decision Making,held at Rutgers University, Spring 2012.

研讨会：人工智能与 OR 关于顺序决策的对话，罗格斯大学，2012 年春季。

• 批准号: 1152008
• 负责人: Warren Powell
• 金额: $ 4.26万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1152008&HistoricalAwards=false
• 关键词: Workshop; Conversation; Between; AI; Sequential

Sequential decision making in the presence of uncertainty arises in problems that span transportation and logistics, energy, health and military operations. Real-world instances of these problems are fundamentally intractable, beyond the reach of our most powerful computers. Parallel research among communities such as operations research and computer science has produced a diversity of algorithmic strategies that offer unique features, but significant language and notational barriers have limited the sharing of ideas. This workshop will consist of a series of conversations so that leading professionals, post-docs and students from both communities will better learn the languages of both communities. A major activity will be the design of challenge problems that benefit from the combined skills of both communities. For example, the problem of optimizing fleets of UAVs is a problem class that would be solved in very different ways by each community. Computer scientists tend to solve these as swarms of loosely coordinated, independent agents. Operations researchers have the tools to optimize these fleets using large-scale optimization, reflecting the perspective of a single controller. If successful, the workshop will lead to avenues for improved collaboration between the operations research and computer science communities, including a roadmap for future collaboration between the two research communities. Ultimately this should lead to increased capabilities for solving problems that have been intractable up to now by exploiting the unique skills that each community brings, most prominently the computational power of machine learning and mathematical programming.

在不确定性存在的情况下，顺序决策出现在跨越运输和物流，能源，健康和军事行动的问题。 这些问题在现实世界中的实例从根本上来说是难以解决的，超出了我们最强大的计算机的能力范围。 运筹学和计算机科学等领域的并行研究产生了各种各样的算法策略，这些策略提供了独特的功能，但严重的语言和符号障碍限制了思想的共享。 该研讨会将包括一系列对话，以便来自两个社区的领先专业人员，博士后和学生更好地学习两个社区的语言。 一项主要活动将是设计挑战性问题，受益于两个社区的综合技能。 例如，优化无人机机队的问题是一个问题类，每个社区将以非常不同的方式解决。 计算机科学家倾向于将这些问题作为一群松散协调的独立代理来解决。 运营研究人员拥有使用大规模优化来优化这些车队的工具，反映了单个控制器的观点。 如果成功的话，研讨会将为改进运筹学和计算机科学界之间的合作开辟道路，包括两个研究界之间未来合作的路线图。最终，这将通过利用每个社区带来的独特技能，最突出的是机器学习和数学编程的计算能力，提高解决迄今为止难以解决的问题的能力。