Modeling the Behavioral Dynamics of Social Action and Coordination

模拟社会行动和协调的行为动力学

• 批准号: 9059115
• 负责人: Michael John Richardson
• 金额: $ 28.53万
• 依托单位: UNIVERSITY OF CINCINNATI
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-25 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9059115
• 关键词: Achievement; Autistic Disorder; Behavior; Behavioral; Behavioral Model; Characteristics; Clinical; Clinical Psychology; Cognitive; Cognitive Science; Communication; Complex; Computers; Differential Equation; Discipline; Emotional; Environment; Estimation Techniques; Event; Functional disorder; Goals; Health; Human; Individual; Joints; Kinesiology; Knowledge; Limb structure; Measures; Mental Health; Methods; Modeling; Motor; Movement; Participant; Pathology; Pattern; Perception; Performance; Persons; Physical activity; Physiological; Population; Prejudice; Premature Birth; Process; Property; Psychologist; Psychology; Research; Research Personnel; Resistance; Robot; Robotics; Role; Schizophrenia; Series; Social Behavior; Social Interaction; Social Perception; Social Psychology; Sports; Stimulus; Structure; System; Systems Theory; Testing; Time; User-Computer Interface; Virtual System; base; design; dynamic system; environmental agent; flexibility; insight; interest; psychologic; self organization; social; social cognition; social model; social movement; success; therapy development

DESCRIPTION (provided by applicant): A fundamental feature of social behavior is the face-to-face or co-present interactions that characterize everyday social activity. The success of such interactions, whether measured in terms of social connection, goal achievement, or the ability of an individual or group of individuals to understand and predict the meaningful intentions and behaviors of others, is not only dependent on the processes of social cognition and perception, but also on the between-person motor coordination that makes such face-to-face and co-present interactions possible. Understanding and modeling the dynamics of social motor coordination, including how it emerges and is maintained over time, as well as how its stable states are activated, dissolved, transformed, and exchanged over time, is therefore an extremely important endeavor. The overall aim of the proposed project is to develop a dynamical modeling strategy for capturing the self-organized behavioral dynamics of goal-directed physical activity among socially coordinated human agents and how the dynamics of such tasks are influenced by physical, information, and task-goal properties. More specifically, the proposed project will build differential equation models of the temporal and spatial patterns that dynamically emerge during a number of different movement based multi-agent action tasks: social rhythmic or repetitive movement and targeting tasks, social object-moving tasks, structured conversation tasks, and a competitive sport task. Employing a systems identification approach to formulate candidate behavioral dynamics models, we will not only capture the steady-state dynamics of the joint and social behaviors investigated, but will also formulate models that capture how parameter tuning and symmetry breaking events fundamentally modify the dynamics of social interaction, including movement sub-roles (e.g., leader-follower) and action sequencing. By recording the limb or whole body movements of participants during the real-world performance of social action tasks, we will evaluate and refine the proposed models using a range of parameter estimation techniques. For some of the social action tasks, we will also test and refine the developed models by implementing them into real-time human-computer interfaces and investigate whether the behavior of real participants is modulated in a qualitatively similarly manner when interacting with model-controlled versus other-participant-controlled task stimuli. By developing a detailed strategy for modeling the dynamics of social action tasks, the proposed project will have a transformative impact on the fields which study social coordination such as cognitive science, social and clinical psychology and robotics by providing researchers with empirical modeling strategies for better apprehending the self-organizing dynamics of goal-directed social activity.

描述（由申请人提供）：社会行为的一个基本特征是表征日常社交活动的面对面或共同互动。这种互动的成功，无论是根据社会联系，目标成就而衡量的，还是个人或一组个人理解和预测他人的有意义的意图和行为的能力，不仅取决于社会认知和感知的过程，而且还取决于在人际关系之间的协调性，使这种面对面的互动和共同互动成为可能。因此，了解和建模社交运动协调的动态，包括随着时间的推移如何出现和保持其稳定状态的激活，溶解，转化和随着时间的流逝，这是一项极为重要的努力。拟议项目的总体目的是制定一种动态建模策略，以捕获社会协调的人类代理人中目标定向体育活动的自组织行为动态，以及此类任务的动态如何受到物理，信息和任务 - 目标属性的影响。更具体地说，拟议的项目将建立在许多基于不同运动的多主体动作任务中动态出现的时间和空间模式的微分方程模型：社交节奏或重复性运动以及针对任务，社交对象的任务，结构化的对话任务以及有竞争性的运动任务。采用系统识别方法制定候选行为动力学模型，我们不仅将捕获所研究的关节和社会行为的稳态动力学，而且还将制定模型，以捕获参数调整和对称性破坏事件如何从根本上修改社交互动的动态，包括运动子功能（例如，领导者，追随者和动作序列）。通过记录参与者在社会行动任务的现实表现中的肢体或全身运动，我们将使用一系列参数估计技术评估和完善所提出的模型。对于某些社会行动任务，我们还将通过将其实施到实时的人类计算机界面中来测试和完善开发的模型，并研究与模型控制的与其他参与者控制的任务刺激相互作用时，实际参与者的行为是否以定性方式进行调节。通过制定详细的策略来建模社会行动任务的动态，该项目将对研究社会协调等领域产生变革性的影响，例如认知科学，社会和临床心理学和机器人技术，通过为研究人员提供经验建模策略，以更好地审议目标指导社会活动的自组织动态。