Exploration in Machine Learning
Michael P. Frank
Program in Symbolic Systems
Stanford University
Stanford, California 94305
December 2, 1990
Abstract
Most researchers in machine learning have built their learning systems
under the assumption that some external entity would do all the
work of furnishing the learning experiences. Recently, however,
investigators in several subfields of machine learning have designed
systems that play an active role in choosing the situations that they
will learn from. Such activity is generally called
exploration. This paper describes a few of these
exploratory learning projects, as reported in the literature,
and attempts to extract a general account of the issues involved in
exploration.
Citation information
M. Frank. ``Exploration in Machine Learning.''
Term paper for Steve Minton, December 1990.
@unpublished{Frank-90d,
author = {Michael Frank},
title = {Exploration in Machine Learning},
note = {Term paper for Computer Science 229, Steve Minton,
Stanford University},
month = dec,
year = 1990
}