Multi-objectivity as a Tool for Constructing Hierarchical Complexity

Abstract. This paper presents a novel perspective to the use of multiobjective 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.

• Type: Conference
• Year: 2003
• Where: GECCO
• Authors: Jason Teo, Minh Ha Nguyen, Hussein A. Abbass
• Keywords: Concept Exhibits Characteristics, Evolutionary Multi-objective Optimization, GECCO 2003, Partial Order Feature