智能办公环境中多Agent模糊Q学习研究  

Research on multi-Agent fuzzy Q-learning in intelligent office environment

作　　者：王海珍[1] 廉佐政[2] 滕艳平[1] 

机构地区：[1]齐齐哈尔大学计算机与控制工程学院计算机系,黑龙江齐齐哈尔161006 [2]齐齐哈尔大学计算中心,黑龙江齐齐哈尔161006

出　　处：《计算机工程与应用》2012年第18期231-235,共5页Computer Engineering and Applications

基　　金：齐齐哈尔大学青年教师科研启动支持计划项目(No.2011k-M05)

摘　　要：目前有关智能办公环境的研究忽视了对建筑环境的考虑,为了给工作人员提供一个节能、舒适、便捷的办公环境,研究了智能办公环境无线网络系统的学习方法,即为系统建立了多智能体(Agent)模型,基于该模型提出了改进的模糊Q学习算法,用于学习用户的行为,以自动控制环境中执行器的动作。通过对环境温度学习的实验,比较了该算法和普通Q学习的MSE(Mean Square Error)值,实验结果表明提出的算法较优。Presently, the research on intelligent office environment neglects the consideration of the building envi- ronment. In order to provide an energy-efficient, comfortable, convenient office environment for staffs, the learning method of wireless network system for intelligent office environment is studied. Namely, a multi-Agent model is established for the system, and on basis of which the improved fuzzy Q-learning algorithm is advanced, which is used to study user behavior in the environment, in order to control user action automatically. By the experiment on the ambient temperature study, the MSE （Mean Square Error） values of the improved fuzzy Q-learning algorithm and the ordinary Q are compared, and the result shows that the proposed algorithm is better.

关 键 词：智能办公环境 多智能体模型 模糊学习算法 自动控制 环境温度 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]