Fuzzy Stochastic Automata for reactive learning and hybrid control

被引：0
|
作者：
Rigatos, GG [1 ]
机构：
[1] Univ Patras, Ind Syst Inst, GR-26500 Patras, Greece
来源：
METHODS AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2002年 / 2308卷
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy Stochastic Automata (FSA) are suitable for the modelling of the reactive (memoryless) learning and for the control of hybrid systems. The concept of FSA is to switch between a fuzzy increase and a fuzzy decrease of the control action according to the sign of the product e e, where e = x - x(d) is the error of the system's output and is its first derivative. The learning in FSA has stochastic features. The applications of FSA concern mainly autonomous systems and intelligent robots.
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页码：366 / 377
页数：12
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