归纳逻辑程序设计是机器学习与逻辑程序设计交叉所形成的一个研究领域,克服了传统机器学习方法的两个主要限制:即知识表示的限制和背景知识利用的限制,成为机器学习的前沿研究课题。首先从归纳逻辑程序设计的产生背景、定义、应用领域及问题背景介绍了归纳逻辑程序设计系统的概貌,对归纳逻辑程序设计方法的研究现状进行了总结和分析,最后探讨了该领域的进一步的研究方向。
Inductive Logic Programming (ILP) is a research area at the intersection of machine learning and logic programming, which overcomes two limitations of traditional machine learning: 1)a limited knowledge representation formalism which is essentially proposition- al logic, and 2)a limited use of substantial background knowledge in the learning process. Up to now,ILP has become the front research area of machine learning. In this paper, background, definition, application domain and problem setting of ILP are introduced, the current re- search of inductive logic programming approaches is summarized and analyzed, and some vital aspects that may be conducted in the future investigations are discussed.