基于DFL的自主学习子空间的公理体系研究  

Axiomatic System of Autonomic Learning Subspace Based on DFL

作　　者：王静[1] 李凡长[1] 

机构地区：[1]苏州大学计算机科学与技术学院,苏州215006

出　　处：《计算机科学》2008年第12期146-147,170,共3页Computer Science

基　　金：国家自然科学基金项目(60775045);江苏省自然基金项目(BK2005027);苏州大学211项目(2118005)

摘　　要：动态模糊逻辑理论是一种新的有效处理动态、不精确、不确定、含糊信息的理论,自主学习历来是教育和心理学家共同关注的一个重要问题,也是当前机器学习领域研究中的一个热点问题。自主学习公理体系研究是自主学习理论及应用研究的基础。利用动态模糊关系,建立自主学习子空间的公理体系。该公理体系由几个相互独立的非常简洁的表达式构成,进一步深化了动态模糊和自主学习理论。Dynamic fuzzy logic theory is a new and effective theory when handling dynamic, imprecise, uncertam, or vague information. Autonomic learning has always been an important issue which is concerned by both edueationalists and psychologists, and it is also a hot issue of machine learning research. Axiomatic system of autonomic learning is the foundation of the theory and application of autonomic learning. By using dynamic fuzzy relations, the axiomatic system of autonomic learning subspace was established. The axiomatic system was constituted by three independent expres- sions, further deepening the theory of dynamic fuzzy logic and autonomic learning.

关 键 词：动态模糊逻辑 自主学习 子空间 动态模糊关系 公理体系 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术] O1-0[自动化与计算机技术—计算机科学与技术]