Collaborative Research: Emotional Sophistication - Studies of Facial Expressions in Decision Making

合作研究：情感复杂度 - 决策中的面部表情研究

• 批准号: 1232676
• 负责人: Piotr Winkielman
• 金额: $ 33.3万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1232676&HistoricalAwards=false
• 关键词: Collaborative; Research; Emotional; Sophistication; Studies

Social and economic decisions cannot be fully explained by "rational" attempts to maximize monetary gain, even in very simple game-theoretic scenarios. Complex emotional processes such as anger, guilt or generosity act as hidden forces that lead to observable actions. Such "non-rational" motivations can drive our own decisions and they affect our beliefs about what motivates others' decisions as well. The goal of this project is to use automatic measurements of dynamic facial expressions, in combination with other measurements such as functional MRI (fMRI) and eye-tracking, to investigate the role of non-rational motivations in social decision making. The core of the approach is to use state-of-the-art computer vision techniques to extract facial actions from video in real-time while participants interact with a computer or with each other, in some cases viewing live video of each others' faces. The investigators will use powerful statistical machine learning techniques to make inferences about the participants' internal emotional states during the interactions. The goal is to use the inferences concerning emotional state (a) to predict participants' behavior; (b) to explain why a decision is made in terms of the hidden forces driving it; and (c) to build autonomous agents that can use this information to drive their interactions with humans. This multidisciplinary project contributes to several fields such as psychology, neuroscience, and economics. First, it develops new methodologies to study decision processes. Second, it uses these methods to test hypotheses about social decision-making and to bridge the gap between observable actions and the internal states that generated them. Third, the investigators intend to make available a dataset and toolset that should be an extremely useful for other investigators analyzing facial expression in multiple contexts. Additionally, automatic and on-line decoding of internal motivational states lays the groundwork for "affectively-aware" interactive computers, or artificial systems that can make inferences about the emotions and intentions of their users. Through the development of these systems, this project will make a significant contribution to the growing field of human-machine interaction.[Supported by Perception, Action and Cognition, Decision, Risk and Management Sciences, and Robust Intelligence]

即使在非常简单的博弈论场景中，社会和经济决策也不能完全用货币收益最大化的“理性”尝试来解释。复杂的情绪过程，如愤怒、内疚或慷慨，都是导致可观察行为的隐藏力量。这种“非理性”的动机可以驱动我们自己的决定，也会影响我们对他人决定动机的信念。该项目的目标是使用动态面部表情的自动测量，结合其他测量，如功能性MRI（fMRI）和眼动跟踪，以研究非理性动机在社会决策中的作用。该方法的核心是使用最先进的计算机视觉技术从视频中实时提取面部动作，同时参与者与计算机或彼此交互，在某些情况下观看彼此面部的实时视频。研究人员将使用强大的统计机器学习技术来推断参与者在互动过程中的内部情绪状态。 我们的目标是使用有关情绪状态的推断（a）预测参与者的行为;（B）解释为什么要根据驱动它的隐藏力量做出决定;（c）建立自主代理，可以使用这些信息来驱动他们与人类的互动。这个多学科项目有助于心理学，神经科学和经济学等多个领域。首先，它开发了新的方法来研究决策过程。其次，它使用这些方法来检验关于社会决策的假设，并弥合可观察到的行为与产生这些行为的内部状态之间的差距。第三，研究人员打算提供一个数据集和工具集，这对其他研究人员在多种情况下分析面部表情非常有用。此外，内部动机状态的自动和在线解码为“情感感知”交互式计算机或人工系统奠定了基础，这些系统可以推断用户的情感和意图。通过这些系统的开发，该项目将为日益增长的人机交互领域做出重大贡献。[由感知、行动和认知、决策、风险和管理科学以及强大的智能支持]