Lamb Maurice, Kallen Rachel W, Harrison Steven J, Di Bernardo Mario, Minai Ali, Richardson Michael J
Center for Cognition, Action and Perception, University of CincinnatiCincinnati, OH, United States.
Department of Kinesiology, University of ConnecticutConnecticut, CT, United States.
Front Psychol. 2017 Jun 28;8:1061. doi: 10.3389/fpsyg.2017.01061. eCollection 2017.
Humans commonly engage in tasks that require or are made more efficient by coordinating with other humans. In this paper we introduce a task dynamics approach for modeling multi-agent interaction and decision making in a pick and place task where an agent must move an object from one location to another and decide whether to act alone or with a partner. Our aims were to identify and model (1) the related dynamics that define an actor's choice to move an object alone or to pass it to their co-actor and (2) the trajectory dynamics of an actor's hand movements when moving to grasp, relocate, or pass the object. Using a virtual reality pick and place task, we demonstrate that both the decision to pass or not pass an object and the movement trajectories of the participants can be characterized in terms of a behavioral dynamics model. Simulations suggest that the proposed behavioral dynamics model exhibits features observed in human participants including hysteresis in decision making, non-straight line trajectories, and non-constant velocity profiles. The proposed model highlights how the same low-dimensional behavioral dynamics can operate to constrain multiple (and often nested) levels of human activity and suggests that knowledge of to move or act during pick and place behavior may be defined by these low dimensional task dynamics and, thus, can emerge spontaneously and in real-time with little a priori planning.
人类通常会参与一些任务，这些任务需要与他人协作才能完成，或者通过与他人协作会变得更高效。在本文中，我们引入了一种任务动力学方法，用于对多智能体在“拾取与放置”任务中的交互和决策进行建模。在该任务中，一个智能体必须将一个物体从一个位置移动到另一个位置，并决定是独自行动还是与伙伴合作。我们的目标是识别并建模：（1）定义一个参与者选择独自移动物体还是将其传递给共同参与者的相关动力学；（2）参与者在移动以抓取、重新放置或传递物体时手部运动的轨迹动力学。通过一个虚拟现实“拾取与放置”任务，我们证明了物体是否传递的决策以及参与者的运动轨迹都可以用行为动力学模型来表征。模拟结果表明，所提出的行为动力学模型展现出了在人类参与者中观察到的特征，包括决策中的滞后现象、非直线轨迹以及非恒定速度曲线。所提出的模型突出了相同的低维行为动力学如何在多个（且通常是嵌套的）人类活动层面上发挥作用以形成约束，这表明在“拾取与放置”行为中关于如何移动或行动的知识可能由这些低维任务动力学所定义，因此，几乎无需先验规划就能自发且实时地出现。
