Accession Number:

ADA142814

Title:

Approaches to Machine Learning.

Descriptive Note:

Interim rept. Jan-Feb 84,

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE

Personal Author(s):

• Langley,P.
• Carbonell,J. G.

Report Date:

1984-02-16

Pagination or Media Count:

19.0

Abstract:

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. Author

Descriptors:

• *LEARNING MACHINES
• *LEARNING
• AUTOMATION
• ACQUISITION
• INFORMATION SYSTEMS
• SKILLS
• COMPUTERS
• OBSERVATION
• SEARCHING
• LANGUAGE
• SYMBOLS

Subject Categories:

• Psychology
• Computer Hardware
• Bionics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE