Collaborative Research: CRCNS Research Proposal: Adaptive Decision Rules in Dynamic Environments

合作研究：CRCNS 研究提案：动态环境中的自适应决策规则

基本信息

批准号：
2207700
负责人：
Zachary Kilpatrick
金额：
$ 24.24万
依托单位：
University of Colorado at Boulder
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2207700&HistoricalAwards=false
关键词：
Collaborative Research CRCNS Proposal Adaptive

项目摘要

When decisions are made, which can be as simple as where to have lunch or as complicated as what career to pursue, time is often spent deliberating over uncertain evidence and possible outcomes. This deliberation process is central to behavioral and cognitive flexibility but requires overcoming a major challenge: determining when to stop deliberating and commit to a course of action. Many models that have been used to study human decision-making and to implement machine decision-making assume that decision commitment occurs when the accumulated evidence reaches a fixed value or bound. These “accumulate-to-bound” models, whose development last century helped formalize and improve decisions related to codebreaking, manufacturing, and other real-world applications, have also provided a useful starting point for understanding decision commitment in the brain. However, fixed bounds are most appropriate under fixed conditions, which are often used in laboratory experiments but rarely encountered in the real world. The goal of this study is to move beyond the “fixed bound” form of decision commitment and instead consider more flexible ways the brain uses to end deliberating and arrive at a decision. The research starts with a new, mathematically grounded theory that describes the advantages of using flexible forms of commitment under changing conditions. The Principal Investigators (PIs) then use this theory to design and interpret experiments that will provide a comprehensive new view of how human brains commit to decisions even when they are based on deliberations that occur during uncertain and changing conditions. This work will provide interdisciplinary training at the interface of mathematics, cognitive science, psychology, and neuroscience for undergraduate and graduate students from diverse backgrounds. The PIs will use research-related activities to encourage the participation of underrepresented groups in science. Also, the PIs will develop and disseminate resources, including novel datasets and analytic tools, that will benefit research and education in how the brain makes decisions. Finally, the PIs will increase public awareness of computational neuroscience and address the urgent need to increase scientific literacy and understanding of how science can benefit society. This will be accomplished via public lectures, contributions to the program “Engines of Our Ingenuity” broadcast by National Public Radio stations nationwide, Brain Awareness Week activities, and contributions to a website that explains brain research to non-specialists. Deliberative decisions free the brain from the immediacy of reflexive processing but pose a critical challenge: how does the brain decide when to stop deliberating and commit to a course of action? Our understanding of this commitment process has been dominated by a computational framework that assumes decisions are terminated once accumulated evidence reaches a predefined level or bound. These “accumulate-to-bound” models have close ties to normative theory and can explain a range of behavioral and neural findings. However, they are optimal only under the highly restrictive conditions used in many decision studies, in which the informativeness, rate of acquisition, and other features of the evidence are stable and known in advance. It is not known how the brain balances decision deliberation and commitment more generally, when temporally extended decisions must contend with our dynamic and uncertain world. The goal is to advance our understanding of the decision rules used by the brain under these conditions. The PIs start with a novel theoretical foundation that includes flexible decision bounds that are not predefined but instead can be updated while the decision is being formed to optimize performance even under changing conditions. They use this framework to guide the design and analysis of behavioral studies in humans and combine behavioral and neurophysiological studies in non-human primates, which they use to test their primary hypothesis that the primate brain uses dynamic, adaptive rules to support rational decision-making in changing and uncertain environments.This project is co-funded by the Division of Mathematical Sciences (DMS) within the Mathematical and Physical Sciences Directorate (MPS), Division of Information and Intelligent Systems (IIS) in the Directorate of Computer and Information Science and Engineering (CISE), and Division of Behavioral and Cognitive Sciences (BCS) within the Directorate for Social, Behavioral, and Economic Sciences (SBE).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.

当做出决定时，这可能很简单，就像在哪里吃午餐或像购买的职业一样复杂时，时间通常会花在不确定的证据和可能的结果上。这种审议过程对于行为和认知灵活性至关重要，但需要克服一个重大挑战：确定何时停止审议并承诺采取行动。许多用于研究人类决策并实施机器决策的模型都认为，当获得的证据达到固定价值或界限时，就会发生决策承诺。这些“累积”模型上世纪的发展帮助正式化和改善了与代码破坏，制造和其他现实世界应用相关的决策，也为了解大脑中的决策承诺提供了有用的起点。但是，在固定条件下，固定界限最合适，在实验室实验中通常使用，但在现实世界中很少遇到。这项研究的目的是超越决策承诺的“固定界限”形式，而是考虑大脑以结束审议和做出决定的更灵活的方式。该研究以一种新的数学基础理论开始，该理论描述了在不断变化的条件下使用灵活形式的承诺形式的优势。然后，主要研究人员（PIS）使用该理论来设计和解释实验，这些实验将为人类大脑如何做出决策提供全面的新观点，即使他们是基于在不确定和不断变化的条件下进行的讨论。这项工作将为来自潜水员背景的本科生和研究生的数学，认知科学，心理学和神经科学的界面提供跨学科培训。 PI将使用与研究相关的活动来鼓励代表性不足的群体参与科学。此外，PI将开发和传播资源，包括新颖的数据集和分析工具，这将使大脑如何做出决策有益于研究和教育。最后，PI将提高公众对计算神经科学的认识，并满足提高科学素养和了解科学如何使社会受益的迫切需求。这将通过公开演讲，全国国家公共广播电台播出的“我们创造力的发动机”计划的贡献，脑意识周的活动以及对向非专家解释大脑研究的网站的贡献。审议决定使大脑摆脱反身处理的立即处理，但构成了一个关键的挑战：大脑何时停止审议和承诺采取行动的决定如何？我们对这一承诺过程的理解是由一个计算框架主导的，该计算框架假设一旦累积证据达到预定义的水平或界限，就会终止决策。这些“积聚”模型与正常理论有着密切的联系，可以解释一系列行为和神经发现。但是，仅在许多决策研究中使用的高度限制性条件下，它们才是最佳选择，在许多决策研究中，信息，获取率和证据的其他特征是稳定且事先知道的。尚不清楚大脑如何平衡决策的审议和承诺，而暂时扩展的决策必须与我们的动态和不确定的世界抗衡。目的是提高我们对在这些条件下大脑使用的决策规则的理解。 PI从一个新颖的理论基础开始，其中包括灵活的决策范围，这些范围不是预定义的，但可以在制定决定时更新以优化绩效，即使在不断变化的条件下也可以优化绩效。 They use this framework to guide the design and analysis of behavioral studies in humans and combine behavioral and neurophysiological studies in non-human primates, which they use to test their primary hypothesis that the primary brain uses dynamic, adaptive rules to support rational decision-making in changing and uncertain environments.This project is co-funded by the Division of Mathematical Sciences (DMS) within the Mathematical and Physical Sciences Directorate (MPS), Division of Information以及计算机和信息科学与工程局（CISE）的智能系统（IIS），以及在社会，行为和经济科学局（SBE）局内行为和认知科学（BCS）的划分。本奖反映了NSF的立法任务，并通过评估通过基金会的知识优点和广泛的评估来进行评估，并被认为是宝贵的。