RI: Large: Collaborative Research: Understanding Uncertainty in Rats and Robots

RI：大型：合作研究：了解老鼠和机器人的不确定性

• 批准号: 0910710
• 负责人: Jeffrey Krichmar
• 金额: $ 79.98万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0910710&HistoricalAwards=false
• 关键词: RI; Large; Collaborative; Research; Understanding

Humans, rats and other vertebrates, relying on their advanced nervous systems, are far superior at dealing with the uncertainties of the world than are artificial systems. Thus, a machine, whose behavior is guided by a neurobiologically inspired system, might demonstrate the flexible, autonomous behavior normally attributed to biological organisms. Biological organisms have the ability to respond quickly to an ever-changing world. Because this adaptability is so critical for survival, all vertebrates have sub-cortical structures, which comprise the neuromodulatory systems, to handle uncertainty and change in the environment. Attention, which is influenced by neuromodulation, plays a significant role in animal's ability to respond to such changes. Different neuromodulatory systems are thought to play important and distinct roles in attention. A collaborative approach, which compares rodent experiments with robots having simulated nervous systems, will examine these attentional systems. These experiments will lead to a better understanding of how animals cope with uncertainty in the environment, and will lead to the design of a robot capable of flexible and complex behavior. This work has the potential of being paradigm-shifting technology that could find its way in many practical applications.In an interdisciplinary approach, a robotic system, whose design is based on the vertebrate neuromodulatory system and its effect on attention, will be constructed and tested under similar experimental conditions to the rat, and then in a more practical application. This approach, which combines computational modeling and robotics with rodent behavioral and electrophysiological experiments, will lead to a better understanding of how areas of the brain allocate attentional resources and cause the organism to respond rapidly to essential events and objects. Two of these neuromodulatory systems, the cholinergic and noradrenergic, are thought to play important and distinct roles in attention. Expected uncertainty, the known degree of unreliability of predictive relationships in the environment, drives activity within the cholinergic system. Unexpected uncertainty, large changes in the environment that violate prior expectations, drives activity within the noradrenergic system. These systems modulate activity in brain areas to properly allocate the attention to stimuli in the environment necessary for adequate learning to occur and fluid behavior to be maintained. This knowledge will be used to construct a robust, intelligent robotic system whose capability to adapt to change, and behave effectively in a noisy, complex environment will rival that of a biological system.

人类、老鼠和其他脊椎动物依靠它们先进的神经系统，在应对世界的不确定性方面远远优于人工系统。因此，一台机器，其行为由神经生物学启发的系统引导，可能会展示出通常归因于生物有机体的灵活、自主的行为。生物有机体有能力对不断变化的世界做出快速反应。由于这种适应性对生存至关重要，所有脊椎动物都有皮质下结构，这些结构组成了神经调节系统，以应对环境中的不确定性和变化。注意力受到神经调节的影响，在动物对这种变化的反应能力中扮演着重要的角色。不同的神经调节系统被认为在注意力中扮演着重要而不同的角色。一种合作的方法，将啮齿类动物的实验与具有模拟神经系统的机器人进行比较，将检查这些注意力系统。这些实验将有助于更好地理解动物如何应对环境中的不确定性，并将导致能够灵活和复杂行为的机器人的设计。这项工作具有转变范式的潜力，可以在许多实际应用中找到方法。在一种跨学科的方法中，将构建一个机器人系统，其设计基于脊椎动物神经调制系统及其对注意力的影响，并在类似于大鼠的实验条件下进行测试，然后在更实际的应用中。这种将计算建模和机器人技术与啮齿动物行为和电生理实验相结合的方法，将有助于更好地理解大脑区域如何分配注意力资源，并使有机体对基本事件和对象做出快速反应。其中两个神经调节系统，胆碱能和去甲肾上腺素，被认为在注意力中扮演着重要而独特的角色。预期不确定性，即环境中预测关系的已知不可靠程度，驱动胆碱能系统内的活动。意想不到的不确定性，环境中违反先前预期的巨大变化，推动去甲肾上腺素系统内的活动。这些系统调节大脑区域的活动，以适当地将注意力分配到环境中的刺激上，这是进行充分学习和保持流畅行为所必需的。这些知识将被用来构建一个强大的、智能的机器人系统，其适应变化的能力，以及在嘈杂、复杂环境中的有效行为将与生物系统相媲美。