Computation Trees - A Generalization of Decision Trees

This book is devoted to the study of deterministic and nondeterministic computation trees. Computation trees are a natural generalization of decision trees: in addition to the one-place predicate-type operations (attributes) used in decision trees, computation trees can use multi-place predicate and function operations. They arise both where we deal with algorithms for solving problems of combinatorial optimization, computational geometry, etc., and where we solve classification or prediction problems, especially if we use combinations of input variables as attributes. This book mainly studies the complexity of computation trees and also examines related optimization problems. The results discussed in this book may be useful to researchers studying algorithms and using algorithm models similar to computation trees. These results may also be useful to researchers working with decision trees and decision rule systems in data analysis, particularly, in rough set theory, logical analysis of data, and test theory. The book is also used to create graduate courses.

List of contents

Introduction.- Computation Trees Over Predicate Structures. Local Approach.- Computation Trees Over Predicate Structures. Global Approach.- Rough Analysis of Computation Trees.- Algorithmic Problems for Computation Trees.- Programs Versus Finite Tree-Programs.

Product details

• Authors: Mikhail Moshkov
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 30.09.2025
• EAN: 9783031917479
• ISBN: 978-3-0-3191747-9
• No. of pages: 165
• Illustrations: XII, 165 p. 5 illus.
• Series: Intelligent Systems Reference Library
• Subjects: Natural sciences, medicine, IT, technology > Technology > General, dictionaries; Regelungstechnik, Optimization, Datenbanken, Control and Systems Theory, Data Engineering, Computational Intelligence, decision trees, Deterministic Computation Trees, Computation Trees, Nondeterministic Computation Trees