Principled Reasoning about Dynamical Systems

关于动力系统的原理推理

• 批准号: RGPIN-2020-05031
• 负责人: Soutchanski, Mikhail
• 金额: $ 1.75万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749916
• 关键词: Principled; Reasoning; about; Dynamical; Systems

Dynamic phenomena are found in a broad range of contexts from discrete event control in technical systems, to business processes, to atoms changing bonds in chemical reactions. Despite their diversity, these dynamic phenomena often have common conceptualization either in terms of discrete transitions affected by actions, or in terms of hybrid systems where there are continuous processes and flows that can be initiated or terminated by discrete actions or events.  What is important these phenomena can be described using common underlying principles. These principles should be formally represented in a mathematical language that facilitates their analysis. This helps to design general solutions that can be subsequently deployed in a variety of applications. The proposed research program contributes to developing general principled representations for actions and their effects, and to demonstrating how these representations can be used to perform computationally tractable reasoning about the direct and indirect effects of actions. There are several conceptual and computational challenges that prevent the existing principled representations and reasoning mechanisms from making practical contributions to solving real-world problems. The proposed research will address some of these remaining challenges. The objective of the proposed research program is  advance our knowledge about specialized reasoning mechanisms that can lead to development of efficient domain independent techniques for solving problems in dynamical systems. This include identifying the kinds of dynamical systems that frequently occur in practical applications and investigating the use of principled logical representations to model these systems. The proposed research will focus on application of specialized reasoning mechanisms to solve large scale planning problems. In particular, there is a need to explore how lifted representations can be used to solve deterministic planning problems when initial knowledge is incomplete. Moreover, I will explore the question how lifted heuristic planning can be done when actions have indirect effects. This is important since in some realistic domains preconditions of actions can be defined using nested abbreviations whose truth values change indirectly when actions are executed. The proposed research will concentrate on the cases where computationally tractable, domain independent techniques can be developed.  Also, I will explore how can we correctly and efficiently determine the actual causes of an observed effect. This task includes finding  not only the primary actual cause, but also the whole causal chain including the root cause of an effect. The outcome of this research will be advancement of our knowledge and the development of techniques with potentially broad applicability.

动态现象存在于广泛的背景下，从技术系统中的离散事件控制到业务流程，再到化学反应中的原子改变键。尽管它们的多样性，这些动态现象往往有共同的概念，无论是在离散的过渡影响的行动，或在混合系统，有连续的过程和流动，可以启动或终止离散的行动或事件。重要的是，这些现象可以用共同的基本原则来描述。这些原则应该用数学语言来正式表示，以便于分析。这有助于设计通用解决方案，随后可以在各种应用程序中部署。拟议的研究计划有助于制定一般原则的表示行动及其影响，并展示这些表示可以用来执行计算上易于处理的推理行动的直接和间接影响。有几个概念和计算的挑战，阻止现有的原则表示和推理机制，使实际的贡献，解决现实世界的问题。拟议的研究将解决这些剩余的challenges.Objective提出的研究计划是推进我们的知识，专门的推理机制，可以导致开发高效的域独立的技术解决问题的动力系统。这包括识别在实际应用中经常出现的动态系统的种类，并研究使用原则性逻辑表示来建模这些系统。建议的研究将集中在应用专门的推理机制来解决大规模规划问题。特别是，有必要探讨如何解除表示可以用来解决确定性规划问题时，初始知识是不完整的。此外，我将探讨如何解除启发式规划的问题时，可以做的行动有间接的影响。这一点很重要，因为在某些现实领域中，可以使用嵌套的缩写来定义动作的前提条件，这些缩写的真值在动作执行时间接改变。拟议的研究将集中在计算上易于处理的情况下，域独立的技术可以开发。此外，我将探讨如何才能正确和有效地确定所观察到的效果的实际原因。这个任务不仅包括找到主要的实际原因，还包括整个因果链，包括结果的根本原因。这项研究的结果将是我们知识的进步和具有潜在广泛适用性的技术的发展。