Title :
Multiresolutional intelligent controller for baby robot
Author :
Albus, J. ; Lacaze, A. ; Meystel, A.
Author_Institution :
Intelligent Syst. Div., US Dept. of Commerce, Boulder, CO, USA
Abstract :
This paper presents an algorithm of unsupervised learning for applications in robotics. Minimum initial knowledge is presumed (“bootstrap knowledge”). The learning system uses the newly arrived information to extract rules of motion and construct the world representation. The concept of recursive generalization is explored as the main tool of rule extraction and knowledge organization. The experiment in learning is described based upon simulation of a 2D and a 3D mobile system
Keywords :
generalisation (artificial intelligence); intelligent control; knowledge engineering; robots; 2D mobile system; 3D mobile system; baby robot; bootstrap knowledge; knowledge organization; minimum initial knowledge; multiresolutional intelligent controller; recursive generalization; rule extraction; unsupervised learning; world representation; Clustering algorithms; Decision making; Intelligent robots; Intelligent sensors; Intelligent systems; Learning systems; Orbital robotics; Pediatrics; Robot control; Robot sensing systems;
Conference_Titel :
Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-2722-5
DOI :
10.1109/ISIC.1995.525060
