- author = "Tuze Kuyucu",
- title = "Evolution of circuits in hardware and the evolvability of artificial development",
- school = "Department of Electronics, University of York",
- year = "2010",
- address = "UK",
- month = jun,
- keywords = "genetic algorithms, genetic programming, cartesian genetic programming, Evolvable hardware, EHW, artificial development, evolutionary computation, bio-inspired computing, gene regulatory network, multicellular organisation",
-
URL = "
http://etheses.whiterose.ac.uk/1020/1/FinalSubmission_Thesis.pdf",
-
URL = "
http://etheses.whiterose.ac.uk/1020/",
- size = "250 pages",
-
abstract = "Automatic design of digital electronic circuits via
evolutionary algorithms is a promising area of
research. When evolved intrinsically on real hardware,
evolved circuits are guaranteed to work and the
emergence of novel and unconventional circuits is
likely. However, evolution of digital circuits on real
hardware can cause various reliability issues. Thus,
key mechanisms that produce reliable evolution of
digital circuits on a hardware platform are developed
and explained in the first part of this thesis.
On the other hand, the evolution of complex and scalable designs without any assistance is thwarted due to increasingly large genomes. Using traditional circuit design knowledge to assist evolutionary algorithms, the evolution of scalable circuits becomes feasible, but the results found in such experiments are neither novel anymore nor are they competitive with engineered designs.
A novel, biologically inspired gene regulatory network based multicellular artificial developmental model is introduced in this thesis. This developmental model is evolved to build digital circuits that can automatically scale to larger designs. However, the results achieved still remain inferior to engineered digital circuit designs.
Evolving a developmental system for the design of engineering systems or computational paradigms provides a variety of desirable properties, such as fault tolerance, adaptivity, and scalable designs automation. However, developmental systems in their role as computational networks are as yet poorly understood. Many mechanisms and parameters that a developmental system comprises are based on various assumptions, their biological counterparts, or educated guesses. There is a lack of understanding of the roles of these mechanisms and parameters in forming an evolvable platform for evolutionary computation.
Initially, various experiments are shown to demonstrate the evolvability of the new developmental system. A thorough investigation is then undertaken in order to obtain large amounts of empirical data that yields a better understanding of some of the crucial developmental mechanisms and parameters on the evolvability of multicellular developmental systems.",
- notes = "Available under License Creative Commons Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales. 6Mb Item Type: Thesis (PhD) ID Code: 1020 Deposited By: Mr. Tuze Kuyucu Deposited On: 16 Feb 2011 12:40 Last Modified: 16 Feb 2011 12:40",
