系统讲解人工智能规划的核心概念与技术，适合初学者入门。
Introduction to AI Planning
- 以状态转移系统建模世界，通过搜索路径实现目标达成
- 涵盖经典规划、约束满足规划及主流的HTN规划方法
- 适合对智能系统设计、自动化调度感兴趣的读者
这是斯图加特大学讲座的讲义，介绍人工智能规划的关键概念与技术。人工智能规划（又称自动规划）始于1966年，为赋予轮式机器人自主性而产生。历经数十年发展，已成为研究与应用并重的领域，常与调度相关。多数方法将世界建模为状态转移系统，规划问题转化为从当前状态到目标状态的路径搜索。讲义首先介绍状态模型，随后探讨经典规划这一基础形式及其求解算法；接着分析将规划视为约束满足问题的方法，说明映射过程与求解策略；最详尽的部分聚焦于层次任务网络（HTN）规划，该技术在领域中应用广泛且功能强大。最后附赠一章关于规划领域定义语言（PDDL），作为非层次规划问题的标准表示语法。
原文摘要 · Abstract (English)
These are notes for lectures presented at the University of Stuttgart that provide an introduction to key concepts and techniques in AI Planning. Artificial Intelligence Planning, also known as Automated Planning, emerged somewhere in 1966 from the need to give autonomy to a wheeled robot. Since then, it has evolved into a flourishing research and development discipline, often associated with scheduling. Over the decades, various approaches to planning have been developed with characteristics that make them appropriate for specific tasks and applications. Most approaches represent the world as a state within a state transition system; then the planning problem becomes that of searching a path in the state space from the current state to one which satisfies the goals of the user. The notes begin by introducing the state model and move on to exploring classical planning, the foundational form of planning, and present fundamental algorithms for solving such problems. Subsequently, we examine planning as a constraint satisfaction problem, outlining the mapping process and describing an approach to solve such problems. The most extensive section is dedicated to Hierarchical Task Network (HTN) planning, one of the most widely used and powerful planning techniques in the field. The lecture notes end with a bonus chapter on the Planning Domain Definition (PDDL) Language, the de facto standard syntax for representing non-hierarchical planning problems.
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