by E. Triantaphyllou, B. Kovalerchuk, and A.S. Deshpande
Interfaces in Computer Science and Operations Research,
(R. Barr, R. Helgason, and J. Kennington, Editors), Kluwer Academic Publishers,
pp. 215-236, (1996).
Abstract:
One of the main areas of great potential in the interface of
operations research and computer science is in inductive
inference. Inductive inference refers to the extraction of a
pattern from observations which belong to different classes.
This is the essence of building many intelligent systems with
learning capabilities. In this paper we discuss a logical
analysis approach to this problem. Given are sets of binary
vectors. The main problem is how to extract a Boolean function,
in CNF or DNF form, with as few clauses (conjunctions or
disjunctions) as possible. Therefore, this is an optimization
problem. We present a number of theoretical results and also
some possible extensions.
Key Words:
Inductive inference, machine learning, learning from examples,
maximum clique, Boolean functions, CNF/DNF form, monotone Boolean
functions.
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