HASLEARN: a highly autonomous system with learning behavior

Author

Chou, Fu-Hua ; Ho, Cheng-Seen

Author_Institution

Dept. of Electron. Eng., Nat. Taiwan Inst. of Technol., Taipei, Taiwan

Volume

1

fYear

1994

fDate

2-5 Oct 1994

Firstpage

108

Abstract

HASLEARN is a highly intelligent autonomous system that contains multistrategy learning capabilities which are integrated by a four-stages incremental learning processes. So HASLEARN can work like a human operator to learn operationalized reactive action rules, to recover and eliminate any accidents or anomalisms, and to learn prediction rules to warn the development of potential, abnormal states based on the current states when it is applied in a nuclear power plant. This paper describes the embedded learning capabilities in the planner component of HASLEARN

Keywords

learning (artificial intelligence); learning systems; planning (artificial intelligence); HASLEARN; anomalism removal; incremental learning; intelligent autonomous system; multistrategy learning; planner; prediction rule learning; reactive action rule learning; Control systems; Electrical equipment industry; Humans; Industrial control; Intelligent systems; Libraries; Manufacturing industries; Monitoring; Predictive models; Road accidents;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-2129-4

Type

conf

DOI

10.1109/ICSMC.1994.399820

Filename

399820