Professor Mikhail Moshkov’s new book published by Springer
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Professor Mikhail Moshkov’s new book, “Computation Trees: A Generalization of Decision Trees,” has been published by Springer.
Moshkov’s 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.
These models arise in areas such as combinatorial optimization, computational geometry, and classification or prediction tasks, particularly when combinations of input variables serve as attributes.
The book mainly studies the complexity of computation trees and examines related optimization problems. Its findings may benefit researchers studying algorithms and using algorithm models similar to computation trees. The book 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. It can also be used to create graduate-level courses.
