Automated evolutionary design of self-assembly and self-organising systems

Terrazas Angulo, German (2009) Automated evolutionary design of self-assembly and self-organising systems. PhD thesis, University of Nottingham.

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (11MB) | Preview

Abstract

Self-assembly and self-organisation are natural construction processes where the spontaneous formation of aggregates emerges throughout the progressive interplay of local interactions among its constituents. Made upon cooperative self-reliant components, self-assembly and self-organising systems are seen as distributed, not necessarily synchronous, autopoietic mechanisms for the bottom-up fabrication of supra-structures. The systematic understanding of how nature endows these autonomous components with sufficient ''intelligence'' to combine themselves to form useful aggregates brings challenging questions to science, answers to which have many potential applications in matters of life and technological advances. It is for this reason that the investigation to be presented along this thesis focuses on the automated design of self-assembly and self-organising systems by means of artificial evolution. Towards this goal, this dissertation embodies research on evolutionary algorithms applied to the parameters design of a computational model of self-organisation and the components design of a computational model of self-assembly. In addition, an analytical assessment combining correlation metrics and clustering, as well as the exploration of emergent patterns of cooperativity and the measurement of activity across evolution, is made. The results support the research hypothesis that an adaptive process such as artificial evolution is indeed a suitable strategy for the automated design of self-assembly and self-organising systems where local interactions, homogeneity and both stochastic and discrete models of execution play a crucial role in emergent complex structures.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Krasnogor, N.
Kendall, G.
Keywords: evolutionary design, self-assembly, self-organisation, self-assembly systems, self-organising systems, genetic algorithms, design optimisation, continuous design optimisation, discrete design optimisation, self-assembly Wang tiles design, cellular automata parameter design, cellular automata rule design, emergent complex structures design, genotype-phenotype-fitness analysis, self-assembly dynamics, cellular automata identification, Wang tiles, cellular automata
Subjects: Q Science > Q Science (General)
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 10648
Depositing User: EP, Services
Date Deposited: 26 Jan 2009
Last Modified: 15 Oct 2017 13:23
URI: https://eprints.nottingham.ac.uk/id/eprint/10648

Actions (Archive Staff Only)

Edit View Edit View