computation

KAUST researchers publish new book on decision rule systems

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KAUST Postdoctoral Research Fellows Kerven Durdymyradov and Azimkhon Ostonov, along with Professor Mikhail Moshkov, have published a new book with Springer titled "Transforming Decision Rule Systems into Decision Trees: Syntactic Approach." The book is devoted to the transformation of decision rule systems into deterministic and nondeterministic decision trees that recognize the properties of these systems. It continues the development of the syntactic approach to the study of the transformation problem, which assumes the input data is unknown and only a system of decision rules exists to be

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