Automatic evaluation and selection of problem-solving methods: Theory and
experiments
Eugene Fink
Journal of
Experimental and Theoretical Artificial Intelligence, 16(2), pages
73-105, 2004.
Abstract
The choice of the right problem-solving method, from available methods,
is a crucial skill for experts in many areas. We present a technique for
automatic selection among methods based on analysis of their past performances.
We formalize the statistical problem involved in choosing an efficient
method, derive a solution to this problem, and describe a selection algorithm.
The algorithm not only chooses among available methods, but also decides
when to abandon the chosen method if it takes too much time. We then
extend the basic statistical technique to account for problem sizes and
similarity among problems.