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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716326
• 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具有共同的概念，要么是受动作影响的离散转换，要么是混合系统，其中存在可以由离散动作或事件启动或终止的连续过程和流程。 重要的是，这些现象可以使用共同的基本原理来描述。这些原理应该用数学语言来正式表示，以便于分析。这有助于设计随后可以部署在各种应用程序中的通用解决方案。拟议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。有一些概念和计算方面的挑战阻碍了现有的原则表示和推理机制为解决现实世界问题做出实际贡献。拟议的研究将解决其中一些剩余的挑战。拟议研究计划的目标是增进我们对专业推理机制的了解，这些机制可以开发有效的领域独立技术来解决动力系统中的问题。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。拟议的研究将侧重于应用专门的推理机制来解决大规模规划问题。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，我将探讨当行动具有间接影响时如何进行启发式规划的问题。这很重要，因为在某些现实领域中，可以使用嵌套缩写来定义操作的先决条件，当操作执行时，其真值会间接改变。拟议的研究将集中于可以开发计算上易于处理的、与领域无关的技术的情况。 此外，我还将探讨如何正确有效地确定观察到的效果的实际原因。这项任务不仅包括找到主要的实际原因，还包括整个因果链，包括影响的根本原因。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开发。