DocumentCode :
2578882
Title :
Machine learning in an asynchronous machine
Author :
Carter, John ; Herath, Jayantha
Author_Institution :
Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
fYear :
1991
fDate :
13-16 Oct 1991
Firstpage :
631
Abstract :
To give a broad view of machine learning, the authors describe the basic methods of learning and give examples of learning systems which illustrate these techniques. Some of the early research in the performance of machine learning systems is discussed. In taking a simplistic approach to machine learning, the techniques are divided into the following categories: rote, inductive, examples, observation and discovery, deduction and analogy. Even by using a simplistic approach these techniques can overlap with each other. High-performance learning machines exhibit more intelligence than low-performance learning machines. Therefore, the performance of a learning algorithm is presented and analyzed with respect to its suitability to a parallel machine environment
Keywords :
inference mechanisms; learning systems; artificial intelligence; deduction; inductive; learning systems; machine learning; parallel machine; rote; Automobile manufacture; Automotive engineering; Engines; Learning systems; Machine learning; Machine learning algorithms; Ovens; Testing; Vehicle driving; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
Conference_Location :
Charlottesville, VA
Print_ISBN :
0-7803-0233-8
Type :
conf
DOI :
10.1109/ICSMC.1991.169756
Filename :
169756
Link To Document :
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