DocumentCode :
291835
Title :
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
Link To Document :
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