SAMY@gmr.COM ("R. Uthurusamy") (03/13/87)
Seminar at the General Motors Research Laboratories in Warren, Michigan.
Friday, March 27, 1987 at 10 a.m.
MACHINE LEARNING : UNIFYING PRINCIPLES and RECENT PROGRESS
RYSZARD S. MICHALSKI
Director of the Artificial Intelligence Laboratory and
Professor of Computer Science and Medical Information Science
University of Illinois, Urbana-Champaign, Illinois 61801
Machine learning, a field concerned with developing computational theories
of learning and constructing learning machines, is now one of the most active
research areas in artificial intelligence. An inference-based theory of
learning will be presented that unifies the basic learning strategies.
Special attention will be given to inductive learning strategies, which
include learning from examples and learning from observation and discovery.
We will show that inductive learning can be viewed as a goal-oriented and
resource-constrained inference process. This process draws upon the
learner's background knowledge, and involves a novel type of inference
rules, called 'inductive inference' rules. In contrast with truth-preserving
deductive rules, inductive rules are falsity-preserving.
Several projects conducted at our AI Laboratory at Illinois will be briefly
reviewed, and illustrated by examples from implemented programs.
Non-GMR personnel interested in attending please contact
R. Uthurusamy [ samy@gmr.com ] 313-986-1989