Principled Reasoning about Dynamical Systems

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变化的键，动态现象存在于广泛的背景中。尽管这些动态现象千差万别，但它们往往具有共同的概念，要么是受行动影响的离散转变，要么是混合系统，在混合系统中，有连续的过程和流可以由离散的行动或事件启动或终止。重要的是，可以使用共同的基本原则来描述这些现象。这些原则应该用一种便于分析的数学语言正式表示。这有助于设计可随后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性表征，并演示如何使用这些表征来执行关于行动的直接和间接影响的易于计算的推理。存在几个概念和计算挑战，阻碍了现有的原则性表示和推理机制为解决现实世界的问题做出实际贡献。拟议的研究将解决其中一些剩余的挑战。提出的研究计划的目标是增进我们对专门推理机制的了解，这些机制可以导致开发出高效的领域无关技术来解决动态系统中的问题。这包括确定在实际应用中经常出现的动力系统的种类，并调查使用原则性逻辑表示法来对这些系统进行建模。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，当初始知识不完整时，需要探索如何使用提升表示法来解决确定性计划问题。此外，我将探讨当行动具有间接影响时，如何进行取消的启发式计划的问题。这一点很重要，因为在某些现实领域中，可以使用嵌套缩写来定义操作的前提条件，当执行操作时，这些缩写的真值会间接更改。拟议的研究将集中在可以开发出计算上易于处理的、与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所观察到的结果的实际原因。这项任务不仅包括找到主要的实际原因，而且还包括整个因果链，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。

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.