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环境中，从技术系统中的离散事件控制到业务流程，再到化学反应中原子改变键，尽管它们具有多样性，但这些动态现象通常在受动作影响的离散转变方面具有共同的概念。 ，或者就存在可以由离散动作或事件启动或终止的连续过程和流的混合系统而言，重要的是这些现象可以使用共同的基本原理来描述。这有助于他们设计通用解决方案。所提出的研究计划有助于开发行动及其影响的一般原则表示，并展示如何使用这些表示来对行动的直接和间接影响进行计算上易于处理的推理。存在一些概念和计算方面的挑战，阻碍了现有的原则性表示和推理机制对解决现实世界问题做出实际贡献。拟议的研究计划的目标是增进我们对这些挑战的了解。专门的推理机制可以导致开发有效的领域独立技术来解决动态系统中的问题，这包括识别实际应用中经常出现的动态系统的类型，并研究使用原则逻辑表示来对这些系统进行建模。特别是，需要探索当初始知识不完整时如何使用提升表示来解决确定性规划问题。此外，我将探讨当行动时如何进行提升启发式规划的问题。这很重要，因为在某些方面。动作的现实领域先决条件可以使用嵌套缩写来定义，其真值在执行动作时会间接变化。此外，我将探讨如何开发可计算的、与领域无关的技术。正确有效地确定观察到的影响的实际原因。这项任务不仅包括找到主要的实际原因，还包括包括影响的根本原因在内的整个因果链。这项研究的结果将是我们的知识和结果的进步。开发具有潜在广泛应用前景的技术适用性。