The ability to learn is one of the most fundamental attributes of
intelligent behavior. Consequently, progress in the theory and computer
modeling of learn- ing processes is of great significance to fields
concerned with understanding in- telligence. Such fields include
cognitive science, artificial intelligence, infor- mation science,
pattern recognition, psychology, education, epistemology, philosophy,
and related disciplines. The recent observance of the silver anniversary
of artificial intelligence has been heralded by a surge of interest in
machine learning-both in building models of human learning and in
understanding how machines might be endowed with the ability to learn.
This renewed interest has spawned many new research projects and
resulted in an increase in related scientific activities. In the summer
of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon
University in Pittsburgh. In the same year, three consecutive issues of
the Inter- national Journal of Policy Analysis and Information Systems
were specially devoted to machine learning (No. 2, 3 and 4, 1980). In
the spring of 1981, a special issue of the SIGART Newsletter No. 76
reviewed current research projects in the field. . This book contains
tutorial overviews and research papers representative of contemporary
trends in the area of machine learning as viewed from an artificial
intelligence perspective. As the first available text on this subject,
it is intended to fulfill several needs.