Bi-criteria optimization problem for decision and inhibitory trees: Cost versus cost

Fawaz Alsolami; Mohammad Azad; Igor Chikalov; Mikhail Moshkov

doi:10.1007/978-3-030-12854-8_8

Bi-criteria optimization problem for decision and inhibitory trees: Cost versus cost

Fawaz Alsolami^*, Mohammad Azad, Igor Chikalov, Mikhail Moshkov

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

In this chapter, we study bi-criteria optimization problem cost versus cost for decision and inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for bi-criteria optimization problem for decision trees, and show how the constructed set can be transformed into the graphs of functions that describe the relationships between the studied cost functions. We extend the obtained results to the case of inhibitory trees. We consider two applications: study of 12 greedy heuristics as algorithms for single- and bi-criteria optimization of decision and inhibitory trees, and study of two relationships for decision trees related to knowledge representation—number of nodes versus depth and number of nodes versus average depth.

Original language	English (US)
Title of host publication	Intelligent Systems Reference Library
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	121-139
Number of pages	19
DOIs	https://doi.org/10.1007/978-3-030-12854-8_8
State	Published - 2020

Publication series

Name	Intelligent Systems Reference Library
Volume	156
ISSN (Print)	1868-4394
ISSN (Electronic)	1868-4408

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus subject areas

General Computer Science
Information Systems and Management
Library and Information Sciences

Access to Document

10.1007/978-3-030-12854-8_8

Cite this

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title = "Bi-criteria optimization problem for decision and inhibitory trees: Cost versus cost",

abstract = "In this chapter, we study bi-criteria optimization problem cost versus cost for decision and inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for bi-criteria optimization problem for decision trees, and show how the constructed set can be transformed into the graphs of functions that describe the relationships between the studied cost functions. We extend the obtained results to the case of inhibitory trees. We consider two applications: study of 12 greedy heuristics as algorithms for single- and bi-criteria optimization of decision and inhibitory trees, and study of two relationships for decision trees related to knowledge representation—number of nodes versus depth and number of nodes versus average depth.",

author = "Fawaz Alsolami and Mohammad Azad and Igor Chikalov and Mikhail Moshkov",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.",

year = "2020",

doi = "10.1007/978-3-030-12854-8_8",

language = "English (US)",

series = "Intelligent Systems Reference Library",

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Bi-criteria optimization problem for decision and inhibitory trees: Cost versus cost. / Alsolami, Fawaz; Azad, Mohammad; Chikalov, Igor et al.
Intelligent Systems Reference Library. Springer Science and Business Media Deutschland GmbH, 2020. p. 121-139 (Intelligent Systems Reference Library; Vol. 156).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Bi-criteria optimization problem for decision and inhibitory trees

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AU - Alsolami, Fawaz

AU - Azad, Mohammad

AU - Chikalov, Igor

AU - Moshkov, Mikhail

PY - 2020

Y1 - 2020

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AB - In this chapter, we study bi-criteria optimization problem cost versus cost for decision and inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for bi-criteria optimization problem for decision trees, and show how the constructed set can be transformed into the graphs of functions that describe the relationships between the studied cost functions. We extend the obtained results to the case of inhibitory trees. We consider two applications: study of 12 greedy heuristics as algorithms for single- and bi-criteria optimization of decision and inhibitory trees, and study of two relationships for decision trees related to knowledge representation—number of nodes versus depth and number of nodes versus average depth.

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SP - 121

EP - 139

BT - Intelligent Systems Reference Library

PB - Springer Science and Business Media Deutschland GmbH

ER -

Bi-criteria optimization problem for decision and inhibitory trees: Cost versus cost

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