Rete算法:研究现状与挑战

产生式规则推理系统因其可理解性、易增删、易修改等特点而被广泛用于各种智能领域，但其规则匹配效率 极其低下，不适合大规模推理。Rete算法通过规则条件共享和保存临时匹配结果大大加速了产生式推理，使其成为 效率最高的产生式推理算法之一。但随着数据规模的日益增大、业务信息的频繁变更以及不完整数据和模糊逻辑的 广泛出现，Rctc算法也面临前所未有的挑战。基于这些背景，对Rctc算法的原理、研究现状与面临的问题进行综述， 指出了Ret e算法的常用改进方法。介绍常见的改进方法，并对其进行分析和比较，最后总结了该算法面临的挑战，指 出了未来的研究方向。

Rete Algorithm;Current Issues and Future Challenge

The production system is widely used in AI. But it's not practicable in large amount of data because of its bad matching efficiency. Rete algorithm,which speeds up the match efficiency by sharing condition elements and reserving temporary matching results, has become one of the most widely used reasoning algorithms for production systems. I}his paper gave a survey about the principles, state of art and facing problems of Rete algorithm. Many prominent improve- menu of Rete algorithmare were analyzed and compared. Finally, it concludes the challenges that Rete faces and the di- rection of future research.