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Uncertainty in action selection and sequencing.

行动选择和顺序的不确定性。

基本信息

批准号：
1792919
负责人：
金额：
--
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1792919
关键词：
Uncertainty action selection sequencing.

项目摘要

The execution of a complex task, comprised of multiple sub-tasks, is a frequent realworldchallenge. Uncertainty in this process will be familiar to anybody that has hadto assemble IKEA furniture for the first time. Sensory and perceptual uncertaintymay be reduced through goal-driven gaze shifts to acquire task-relevant informationat the right time. The planning of larger scale movements (e.g. reaching) underconditions of uncertainty is thought to involve competition between multiple motorprogrammes. The gradual resolution of this competition is reflected in characteristicreach-paths. As such, movements of both gaze and limbs may provide insight intothe agent's level of uncertainty at a particular point in time during task execution.However, while gaze has been studied in naturalistic sequential tasks, most of thework on uncertainty in motor planning involves simple, "single-shot" movements. Thechallenge taken up here in this project is to understand and model uncertainty atdifferent levels in the hierarchy of decision making, from goal and sub-goal planningdown to basic movements. We will introduce different forms of uncertainty in thecontext of complex, sequential tasks and use continuous measurement paradigms toidentify uncertainty and its resolution from motor behaviour. Beyond basic theoreticaland empirical interest, this work has the potential to inform the fields of robotics andhuman-computer interaction, as well as to supplement novel delivery methods fortraining in technical and/or complex tasks.

由多个子任务组成的复杂任务的执行是现实世界中经常遇到的挑战。对于任何第一次组装宜家家具的人来说，这个过程中的不确定性都是熟悉的。通过目标驱动的凝视转移，在正确的时间获取与任务相关的信息，可以减少感觉和知觉的不确定性。在不确定条件下规划更大规模的运动(例如到达)被认为涉及多个汽车方案之间的竞争。这场竞争的逐步解决反映在特有的可及路径上。因此，凝视和四肢的运动可能会让我们洞察到代理人在任务执行过程中特定时间点的不确定性水平。然而，虽然凝视已经在自然顺序任务中进行了研究，但大多数关于运动规划中的不确定性的工作都涉及简单的“单发”动作。这个项目面临的挑战是理解决策制定不同层次上的不确定性并对其进行建模，从目标和子目标规划到基本动作。我们将在复杂的顺序任务中引入不同形式的不确定性，并使用连续测量范式来识别不确定性及其从运动行为中的解决方案。除了基本的理论和经验兴趣之外，这项工作还有可能为机器人学和人机交互领域提供信息，并补充技术和/或复杂任务培训的新交付方法。