DocumentCode
1738233
Title
Properties of learning knowledge-based controllers for robotic workcells and dynamic systems
Author
Grant, Edward ; Lee, Gordon K.
Author_Institution
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
Volume
2
fYear
2000
fDate
2000
Firstpage
1216
Abstract
This paper addresses the field of knowledge-based systems, and in particular the sub-field of knowledge-based control systems. The rule-based approach used, particularly in its machine-learning or rule-induction mode, continues as a major theme in the emerging field of data mining - i.e. the extraction of usable insights from large databases
Keywords
data mining; industrial robots; intelligent control; learning (artificial intelligence); learning systems; very large databases; data mining; dynamic systems; knowledge-based controllers; knowledge-based systems; large databases; machine learning; robotic workcells; rule induction; rule-based approach; usable insight extraction; Aerodynamics; Control systems; Data mining; Equations; Humans; Intelligent robots; Knowledge engineering; Machine learning; Robot control; Sensor arrays;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location
Nashville, TN
ISSN
1062-922X
Print_ISBN
0-7803-6583-6
Type
conf
DOI
10.1109/ICSMC.2000.886018
Filename
886018
Link To Document