Conference: Artificial Intelligence Summer School for Computer Science and Operations Research Education; College Park, Maryland; 19-24 May 2024

本拨款用于支持计算机科学与运筹学教育人工智能暑期学校的召开；马里兰大学帕克；2024年5月19日至24日。这是一所暑期学校，面向来自运筹学（OR）和计算机科学（CS）领域的学生和研究人员，帮助弥合运筹学和计算机科学在推进人工智能（AI）研究方面的差距。优化方法是许多支持人工智能的技术的核心。一般来说，OR社区的优化方法是从基础操作挑战中发展起来的，从基于模型的角度开始，而CS社区则从计算、数据驱动的角度开始，应对大量数据集可用性的增加。这两种观点都有很多可以相互借鉴的地方，但到目前为止，它们是分开发展的。暑期学校旨在突出这两种观点，并指导研究生在推进人工智能研究的过程中理解这两种观点的价值。这项资助为来自美国各地的早期博士生提供支持，让他们参加由来自OR和CS社区的人工智能领域的学术研究人员组织的为期一周的暑期学校。暑期学校的主题将集中在强化学习和公平/公平上，由OR和CS的研究人员团队专门为这个场合开发了教程材料。目的是拓宽学生对这两个领域的知识和意识，并在这两个领域的界面上为未来的研究奠定基础。组织者将广泛宣传暑期学校，并将在两个领域实现同等出勤率。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This grant provides funding to support the convening of Artificial Intelligence Summer School for Computer Science and Operations Research Education; College Park, Maryland; 19-24 May 2024. A summer school for students and researchers from the fields of operations research (OR) and computer science (CS) to assist in bridging the gap between the OR and CS perspectives on advancing artificial intelligence (AI) research. Optimization methods are at the core of many techniques that support AI. Generally speaking, the OR community, where optimization methods developed from foundational operational challenges, begins from a model-based perspective, while the CS community, responding to the rise in availability of massive data sets, begins from a computational, data-driven perspective. Both perspectives have much to teach and learn from each other, but to date, they have evolved separately. The Summer School is intended to highlight both perspectives and to guide graduate students in understanding the value of both perspectives as they advance AI research. This grant provides support for early-phase PhD students from across the US to attend a week-long summer school organized by academic researchers in the field of AI from both OR and CS communities. The topics for the summer school will focus on reinforcement learning and fairness/equity, with tutorial material developed especially for the occasion jointly by teams of OR and CS researchers. The intent is to broaden the knowledge and awareness of the students to both fields and to seed future research at the interface of both fields. The organizers will advertise the summer school widely and will target equal attendance across both fields.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.