A Conceptual Model of Adaptive Knowledge-Based Systems
成果类型：
Article
署名作者：
Deng, Pi-Sheng; Chaudhury, Abhijit
署名单位：
California State University System; California State University Stanislaus; University of Massachusetts System; University of Massachusetts Boston
刊物名称：
INFORMATION SYSTEMS RESEARCH
ISSN/ISSBN：
1047-7047
DOI：
10.1287/isre.3.2.127
发表日期：
1992
页码：
127-149
关键词：
摘要：
The ability to learn or adapt is widely recognized as one of the most prominent abilities of any animate or inanimate intelligent system. While considerable progress has been made in the science and technology of machine learning, little of that has been incorporated in traditional knowledge-based systems such as diagnostic or expert systems operating in a managerial environment. In this paper a conceptual model of an adaptive expert system is proposed as an attempt to lay a foundation for building knowledge-based systems that can learn by interacting with the environment. In contrast to existing models for learning (such as for knowledge acquisition and skill refinement) where the issue of noise and uncertainty, is usually neglected. our model incorporates a stochastic environment and a learning response behavior which too is stochastic in nature.
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