New applications of learning automata-based techniques in real-world environments

被引：3

作者：

Rezvanian, Alireza ^{[1
,2
]}

Vahidipour, S. Mehdi ^{[3
]}

Esnaashari, Mehdi ^{[4
]}

机构：

[1] Inst Res Fundamental Sci IPM, Sch Comp Sci, Tehran, Iran

[2] Amirkabir Univ Technol, Tehran Polytech, Comp Engn & Informat Technol Dept, Tehran, Iran

[3] Univ Kashan, Fac Elect & Comp Engn, Comp Engn Dept, Kashan, Iran

[4] KN Toosi Univ Technol, Fac Comp Engn, Tehran, Iran

来源：

JOURNAL OF COMPUTATIONAL SCIENCE | 2018年 / 24卷

关键词：

Computational science; Artificial intelligence; Learning automata; Cellular learning automata; COMPUTATIONAL SCIENCE;

D O I：

10.1016/j.jocs.2017.11.012

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Learning automaton (LA) as a promising technique of artificial intelligence is a self-adaptive decision making device that interacts with an unknown stochastic environment and is progressively able to make optimal decisions even if provided with probabilistic wrong hints. LA has made a significant impact in many areas of computational science as well as engineering problems. The special issue on new applications of learning automata-based techniques in real-world environments for journal of computational science aims at collecting some of the most recent researches regarding theories, structures, and appliances of LA in real-world problems. This editorial summarizes the papers accepted in the special issue. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：287 / 289

页数：3

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