REU Site: Exploring the Limits of Intelligent Systems

REU 网站：探索智能系统的极限

• 批准号: 2243941
• 负责人: Alexandra Schofield
• 金额: $ 39.35万
• 依托单位: Harvey Mudd College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243941&HistoricalAwards=false
• 关键词: REU; Site; Exploring; Limits; Intelligent

REU Site: Exploring the Limits of Intelligent Systems (#2243941)As machine learning and AI systems become ever more common, encroaching on every aspect of society, the need for understanding the systems and their fundamental limitations becomes even more pressing. This project promotes the progress of science and supports education and diversity by training undergraduate students to research questions on the limits of intelligent systems. It builds a cohort of undergraduate students who can develop research ability, presentation skills, and further interest in research-related computing careers. The project focuses on understanding the boundaries in what intelligent systems can achieve both theoretically and in complex real-world scenarios with non-expert users. By educating undergraduate students to probe and understand the limits of these systems, the project helps build an empowered citizenry capable of grappling with the complex ethical and social issues these systems present. Through this award, students will work on cutting-edge subprojects in computer vision, programming language analysis and synthesis, human-robot interaction, and information-theoretic understanding of machine learning systems. These research topics give students valuable academic and industry skills that extend beyond current AI models and frameworks towards the broader reaches of what computing may achieve in the future. The topics for this project are designed to be modular and hierarchical to enable successful undergraduate research milestones. Students will be housed at Harvey Mudd College, an undergraduate-only institution, and experience the most compelling aspects of a graduate school environment during a ten-week summer program. Students will actively engage with the entire research process, from literature search, to articulating problems of interest, to investigations of specific pieces of these problems, and focusing results for presentation and publication.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.

REU 网站：探索智能系统的局限性 (#2243941) 随着机器学习和人工智能系统变得越来越普遍，渗透到社会的各个方面，了解系统及其基本局限性的需求变得更加紧迫。该项目通过培训本科生研究智能系统极限问题来促进科学进步并支持教育和多样性。它培养了一批本科生，他们可以培养研究能力、演讲技巧以及对与研究相关的计算机职业的进一步兴趣。该项目的重点是了解智能系统在理论上和非专家用户的复杂现实场景中可以实现的边界。通过教育本科生探索和理解这些系统的局限性，该项目有助于培养有能力的公民，使其能够应对这些系统带来的复杂的道德和社会问题。通过该奖项，学生将致力于计算机视觉、编程语言分析和综合、人机交互以及机器学习系统的信息理论理解等领域的尖端子项目。这些研究主题为学生提供了宝贵的学术和行业技能，这些技能超越了当前的人工智能模型和框架，延伸到了未来计算可能实现的更广泛的领域。该项目的主题被设计为模块化和分层的，以实现成功的本科生研究里程碑。学生将被安置在哈维穆德学院（Harvey Mudd College），这是一所仅限本科生的机构，并在为期十周的暑期课程中体验研究生院环境中最引人注目的方面。学生将积极参与整个研究过程，从文献检索，到阐明感兴趣的问题，到对这些问题的具体部分进行调查，并集中展示和出版结果。该奖项反映了 NSF 的法定使命，并被认为值得支持通过使用基金会的智力优点和更广泛的影响审查标准进行评估。

项目成果

From Targets to Rewards: Continuous Target Sets in the Algorithmic Search Framework

从目标到奖励：算法搜索框架中的连续目标集

• DOI: 10.5220/0012370600003636
• 发表时间: 2024-02
• 期刊: Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
• 作者: Knell, Milo;Rane, Sahil;Bicker, Forrest;Che, Tiger;Wu, Alan;Montañez, George
• 通讯作者: Montañez, George