Time and space complexity of deterministic and nondeterministic decision trees

In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe. We consider the notion of a problem over information system, which is described by a finit...

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Veröffentlicht in:Annals of mathematics and artificial intelligence Jg. 91; H. 1; S. 45 - 74
1. Verfasser: Moshkov, Mikhail
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.02.2023
Springer
Springer Nature B.V
Schlagworte:
Algorithms
Artificial Intelligence
Complex Systems
Complexity
Computer Science
Decision trees
Information systems
Mathematical analysis
Mathematics
Nodes
Polynomials
Problem solving
Universe
Space complexity
Deterministic decision trees
Time complexity
Nondeterministic decision trees
Time-space trade-off
Complexity classes
ISSN:1012-2443, 1573-7470
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Zusammenfassung:In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe. We consider the notion of a problem over information system, which is described by a finite number of attributes and a mapping associating a decision to each tuple of attribute values. As algorithms for problem solving, we use deterministic and nondeterministic decision trees. As time and space complexity, we study the depth and the number of nodes in the decision trees. In the worst case, with the growth of the number of attributes in the problem description, (i) the minimum depth of deterministic decision trees grows either almost as logarithm or linearly, (ii) the minimum depth of nondeterministic decision trees either is bounded from above by a constant or grows linearly, (iii) the minimum number of nodes in deterministic decision trees has either polynomial or exponential growth, and (iv) the minimum number of nodes in nondeterministic decision trees has either polynomial or exponential growth. Based on these results, we divide the set of all infinite binary information systems into five complexity classes, and study for each class issues related to time-space trade-off for decision trees.
Bibliographie:ObjectType-Article-1
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ISSN:1012-2443
1573-7470
DOI:10.1007/s10472-022-09814-1