Collaborative Research: Integrating dynamic decision making with neurocontrollers by combining system and cognitive sciences

本研究的目的是开发新的神经网络结构，以解决动态决策的最优控制问题。这些问题是相当复杂的，因为系统动态可以在未知的时间切换模式基于事件的决策。方法是从认知科学原理中发展决策范式，但它们的数学表示将使用决策场理论。他们的解决方案包含在神经网络将相互作用的另一组网络，嵌入解决方案的相关最优控制问题制定在一个近似的动态规划framework.Intellectual优点本研究旨在找到统一的控制器解决方案的问题，有连续和离散元素在其中。预计数学认知科学思想的发展将导致新的表示和解决问题的结构在计算神经科学和控制。在这项努力中提出的工作旨在通过提供一种整合系统科学和认知科学概念的变革方法来实现这些目标。通过这项研究开发的更广泛的影响抽象和解决方案结构可用于后果或应急管理系统，如管理地震的后果，恢复受损飞机的稳定性和可持续运动和着陆，以及管理多个资产和分配，以应对威胁。这项研究产生的决策结构也可以对人机交互产生巨大影响。例如，可以开发驾驶员辅助系统来增强人的感知，并在他们在受损条件下驾驶时增强他们的认知。

Project SummaryThe objective of this research is to develop new neural network structures to solve optimal control problems with dynamic decision making. These problems are quite complex since the system dynamics could switch modes at unknown times based on event based decision making. The approach is to develop the decision-making paradigms from cognitive science principles but their mathematical representations will use Decision Field Theory. Their solutions contained in neural networks will interact with another set of networks that embed solutions to the related optimal control problem formulated in an approximate dynamic programming framework.Intellectual Merit This research seeks to find unified controller solutions to problems which have both continuous and discrete elements in them. It is expected that the mathematical cognitive science ideas developed will lead to new representations and problem solving structures in computational neuroscience and control. The work proposed in this effort seeks to accomplish these objectives by offering a transformative approach that integrates concepts from system science and cognitive science. Broader Impact Abstractions and solution structures developed through this research can be used in consequence or emergency management systems like managing the aftermath of an earthquake, retrieving an impaired aircraft to stability and sustainable motion and landing, and managing multiple assets and allocation in striking responses to threats. Decision making structures resulting from this research can make tremendous impact on human-machine interactions too. For example, driver aid systems can be developed to augment human perception and enhance their cognition when they drive under impaired conditions.