Agent普适机器学习模型设计研究

Agent Pervasive Machine Learning Model Design Research

从上世纪90年代Mark Weiser提出普适计算的透明化和不可见性两个特点开始,到2003年国际普适计算会议提出使用自身的信息来提高系统性能以后,普适计算开始向机器学习的方向发展。通过Agent的移动性和普适计算的随时随地性来实现机器学习为各行各业服务的普适功能,从而形成Agent普适机器学习基本内容。借助普适计算的基本性质,结合机器学习的特点,给出Agent普适机器学习设计方法。

Pervasive Computing has developed towards machine learning, since Mark Weiser provided Pervasive Computing from 1990s to 2003 in the international Pervasive Computing conference proposed to improve the system performance using self information. This thesis presents a method of Agent Pervasive machine learning design by means of the basic characteristic of pervasive computing and combing the characteristic of machine learning. For machine learning ＇pervasive ability to service every field by the mobility of Agent and pervasive computing characteristic of Agent pervasive machine learning.