Open Access
Lecture Notes in Computer Science, pages 483-494
Multi-objectivity as a Tool for Constructing Hierarchical Complexity
Publication type: Book Chapter
Publication date: 2003-01-01
Journal:
Lecture Notes in Computer Science
Q2
SJR: 0.606
CiteScore: 2.6
Impact factor: —
ISSN: 03029743, 16113349, 18612075, 18612083
Abstract
This paper presents a novel perspective to the use of multi-objective optimization and in particular evolutionary multi-objective optimization (EMO) as a measure of complexity. We show that the partial order feature that is being inherited in the Pareto concept exhibits characteristics which are suitable for studying and measuring the complexities of embodied organisms. We also show that multi-objectivity provides a suitable methodology for investigating complexity in artificially evolved creatures. Moreover, we present a first attempt at quantifying the morphological complexity of quadruped and hexapod robots as well as their locomotion behaviors.
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TEO J., Nguyen M. H., ABBASS H. A. Multi-objectivity as a Tool for Constructing Hierarchical Complexity // Lecture Notes in Computer Science. 2003. pp. 483-494.
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TEO J., Nguyen M. H., ABBASS H. A. Multi-objectivity as a Tool for Constructing Hierarchical Complexity // Lecture Notes in Computer Science. 2003. pp. 483-494.
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TY - GENERIC
DO - 10.1007/3-540-45105-6_60
UR - https://doi.org/10.1007/3-540-45105-6_60
TI - Multi-objectivity as a Tool for Constructing Hierarchical Complexity
T2 - Lecture Notes in Computer Science
AU - TEO, JASON
AU - Nguyen, Minh Ha
AU - ABBASS, HUSSEIN A.
PY - 2003
DA - 2003/01/01
PB - Springer Nature
SP - 483-494
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
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@incollection{2003_TEO,
author = {JASON TEO and Minh Ha Nguyen and HUSSEIN A. ABBASS},
title = {Multi-objectivity as a Tool for Constructing Hierarchical Complexity},
publisher = {Springer Nature},
year = {2003},
pages = {483--494},
month = {jan}
}