扩展规划库支持高阶建模，让复杂任务更易表达
Towards High-Level Modelling in Automated Planning
- 新增数组类型与布尔计数表达式，增强问题描述能力
- 支持动作中使用整数参数，提升模型灵活性
- 适用于需要复杂逻辑建模的自动化规划场景
规划是众多场景中常见的重要活动，从日常任务到工业流程均涉及。其目标是基于初始状态选择一系列动作以达成指定目标。目前自动化规划领域主流建模语言为规划域定义语言（PDDL），但其表达能力存在局限。本文旨在提升自动化规划系统处理复杂问题的能力。Unified-Planning 是一个 Python 库，提供高层 API 用于定义规划问题并调用求解器。本文提出对 UP 库的扩展，增强其在高阶建模方面的表达力，具体包括：引入数组类型、添加布尔值计数表达式，以及允许动作中使用整数参数。这些改进使得三类经典规划问题可被更自然地建模。
原文摘要 · Abstract (English)
Planning is a fundamental activity, arising frequently in many contexts, from daily tasks to industrial processes. The planning task consists of selecting a sequence of actions to achieve a specified goal from specified initial conditions. The Planning Domain Definition Language (PDDL) is the leading language used in the field of automated planning to model planning problems. Previous work has highlighted the limitations of PDDL, particularly in terms of its expressivity. Our interest lies in facilitating the handling of complex problems and enhancing the overall capability of automated planning systems. Unified-Planning is a Python library offering high-level API to specify planning problems and to invoke automated planners. In this paper, we present an extension of the UP library aimed at enhancing its expressivity for high-level problem modelling. In particular, we have added an array type, an expression to count booleans, and the allowance for integer parameters in actions. We show how these facilities enable natural high-level models of three classical planning problems.
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