基于事例的推理(CBR)研究综述

基于事例的推理(CBR)作为一种增量式的学习方法,规避了传统人工智能在知识获取上的瓶颈问题,逐渐引起人工智能领域研究者的关注。对基于事例的推理(CBR)现有研究工作进行逻辑上的梳理和系统的总结,有助于今后研究工作的开展,具有深远的理论意义。该文首次提出基于事例的推理(CBR)研究的逻辑体系结构,并在此逻辑分析的基础上,从基本理论、关键技术和实践应用三方面进行了综述,对其中关键、通用的方法和技术进行了比较和评价。最后,对未来的研究方向进行了展望。

Review of Case-based Reasoning

As an incremental learning system,case -based reasoning makes the knowledge and rule obtainment bottleneck easy by learning from cases,thus it has increasingly become a hotspot in the area of artificial intelligent.It is significant and great helpful for the future research that reviewing the overall research work logically and systematically.This paper puts forward the structure of logical system originally,and then reviews the development of case -based reasoning from three aspects—— — foundational theory,key technologies and practical utilizing—— — based on logistic analysis,which may enable us get completely comprehension of CBR.At the same time ,issues and problems of CBR deserved to investigate in future is put forward.