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：随着机器学习和AI系统变得越来越普遍，探索智能系统的限制（＃2243941），侵犯了社会的各个方面，了解系统及其基本局限性的需求变得更加紧迫。该项目促进了科学的进步，并通过培训本科生来研究有关智能系统极限的问题，从而支持教育和多样性。它建立了一系列本科生，他们可以发展研究能力，演示技巧以及对与研究相关的计算职业的进一步兴趣。该项目的重点是了解智能系统可以在理论上和在复杂的现实世界中与非专家用户实现的边界。通过教育本科生探究和了解这些系统的局限性，该项目有助于建立能够努力应对这些系统所构成的复杂道德和社会问题的有能力的公民。通过该奖项，学生将在计算机视觉，编程语言分析和综合，人类机器人互动以及对机器学习系统的信息理论理解方面致力于尖端的子项目。这些研究主题为学生提供了有价值的学术和行业技能，这些技能超出了当前的AI模型和框架，可以将来更广泛地实现。该项目的主题旨在模块化和分层，以实现成功的本科研究里程碑。学生将被安置在只有本科机构的哈维·穆德学院（Harvey Mudd College），并在为期十周的夏季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，从文献搜索到表达感兴趣的问题，再到对这些问题的特定部分的调查，并将结果集中在演讲和出版中。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的审查标准来通过评估来通过评估来支持的。

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
• 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