We present Score, a rule engine designed and implemented for the Scone knowledge base system. Scone is a knowledge base system designed for storing and manipulating rich representations of general knowledge in symbolic form. It represents knowledge in the form of nodes and links in a network structure, and it can perform basic inference about the relationships between different elements efficiently. On its own, Scone acts as a sort of "smart memory" that can interface with other software systems. One area of improvement for Scone is how useful it can be in supplying knowledge to an intelligent agent that can use the knowledge to perform actions and update the knowledge base with its observations. We augment the Scone system with a production rule engine that automatically performs simple inference based on existing and newly-added structures in Scone's knowledge base, potentially improving the capabilities of any planning systems built on top of Scone. Production rule systems consist of "if-then" production rules that try to match their predicates to existing knowledge and fire their actions when their predicates are satisfied. We propose two kinds of production rules, if-added and if-needed rules, that differ in how they are checked and fired to cover multiple use cases. We then implement methods to efficiently check and fire these rules in a large knowledge base. The new rule engine is not meant to be a complex stand-alone planner, so we discuss how it fits into the context of Scone and future work on planning systems.

翻译：本文介绍Score，一个专为Scone知识库系统设计并实现的规则引擎。Scone是一个知识库系统，旨在以符号形式存储和操作通用知识的丰富表示。它将知识表示为网络结构中的节点与链接，并能高效执行不同元素间关系的基本推理。就其本身而言，Scone充当一种可与其它软件系统交互的"智能存储器"。Scone的一个待改进方向在于如何更有效地为智能体提供知识，使其能基于知识执行动作并利用观察结果更新知识库。我们通过引入产生式规则引擎增强Scone系统，该引擎能基于知识库中现有及新增结构自动执行简单推理，从而可能提升任何构建于Scone之上的规划系统的能力。产生式规则系统由"如果-那么"形式的产生式规则组成，这些规则试图将其谓词与已有知识匹配，并在谓词满足时触发相应动作。我们提出了两类产生式规则：if-added规则与if-needed规则，二者在检查与触发机制上存在差异，以覆盖多种用例。随后，我们实现了在大规模知识库中高效检查与触发这些规则的方法。该新规则引擎并非设计为复杂的独立规划器，因此我们讨论了它如何融入Scone体系以及未来在规划系统方面的工作。