Fast learning automata for high-speed real-time applications

被引：0

作者：

Obaidat, MS ^{[1
]}

Papadimitriou, GI ^{[1
]}

Pomportsis, AS ^{[1
]}

机构：

[1] Monmouth Univ, Dept Comp Sci, Long Branch, NJ 07764 USA

来源：

ICECS 2000: 7TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS & SYSTEMS, VOLS I AND II | 2000年

关键词：

real-time applications; learning automata; low complexity; high performance;

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：

A new learning automaton which is capable of supporting high speed real-time applications is introduced. The proposed learning automaton has a unique characteristic: it is capable of performing both probability updating and action selection with a computational complexity which is independent of the number of actions. Apart from its low computational complexity, the proposed automaton is capable of achieving a high performance when operating in nonstationary stochastic environments.

引用

页码：633 / 636

页数：4

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