On the role of search for learning from examples
Gold (1967) discovered a fundamental enumeration technique, the so-called identification-by-enumeration, a simple but powerful class of algorithms for learning from examples (inductive inference). We introduce a variety of more sophisticated (and more powerful) enumeration techniques and characterize their power. We conclude with the thesis that enumeration techniques are even universal in that each solvable learning problem in inductive inference can be solved by an adequate enumeration technique. This thesis is technically motivated and discussed.
learning from examples enumeration techniques learning by search identification by enumeration