Autonomic Learning Model and Algorithm Based on DFL

Jing Wang, Fanzhang Li
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引用次数: 9

Abstract

Autonomic learning (AL) refers to an inner mechanism of self-directed learning integrated by learner's attitude, capability and learning strategy. AL usually means active, self-conscious and independent learning, which is opposite to the type of passive, mechanical or receptive learning. AL has always been a hot issue of machine learning research. In this paper, based on the theory of dynamic fuzzy logic (DFL), autonomic learning model and algorithm are developed, which provide a theoretical basis for the people to solve this type of problem. Simulation results illustrate the efficiency of this autonomic learning method.
基于DFL的自主学习模型与算法
自主学习是指学习者的学习态度、学习能力和学习策略三者综合形成的自主学习的内在机制。人工智能通常意味着主动的、自我意识的和独立的学习,与被动的、机械的或接受性的学习类型相反。人工智能一直是机器学习研究的热点问题。本文以动态模糊逻辑(DFL)理论为基础,建立了自主学习模型和算法,为人们解决这类问题提供了理论依据。仿真结果表明了这种自主学习方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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