将答案集编程扩展至动态领域，支持时序与度量约束推理
Computational methods for Dynamic Answer Set Programming
- 融合动态、时序与度量逻辑到答案集编程框架
- 实现复杂动态问题的统一建模与高效推理
- 适合工业场景中的调度、路由等实时决策任务
在日常生活和工业场景中，我们经常面临需要随时间推移进行推理并满足度量约束的动态问题，如调度、路径规划和生产排序。传统动态逻辑虽能应对此类需求，但往往缺乏灵活性与综合建模能力。本研究旨在将答案集编程（ASP）这一强大的声明式求解方法拓展至动态领域，通过整合动态逻辑、时序逻辑与度量逻辑，构建能够有效建模复杂动态问题并执行高效推理的系统，从而提升ASP在工业应用中的适用性。
原文摘要 · Abstract (English)
In our daily lives and industrial settings, we often encounter dynamic problems that require reasoning over time and metric constraints. These include tasks such as scheduling, routing, and production sequencing. Dynamic logics have traditionally addressed these needs but often lack the flexibility and integration required for comprehensive problem modeling. This research aims to extend Answer Set Programming (ASP), a powerful declarative problem-solving approach, to handle dynamic domains effectively. By integrating concepts from dynamic, temporal, and metric logics into ASP, we seek to develop robust systems capable of modeling complex dynamic problems and performing efficient reasoning tasks, thereby enhancing ASPs applicability in industrial contexts.
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