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Inspired by Nature

Part of the Emergence, Complexity and Computation Book Series (volume 28)

Editors: Stepney, Susan; Adamatzky, Andrew

DOI: 10.1007/978-3-319-67997-6

ISBN: 978-3-319-67996-9

Publisher: Springer International Publishing - Springer Journals

Oct 27, 2017

1 - 10 of 17 Chapters

Available

Evolvable Hardware Challenges: Past, Present and the Path to a Promising Future

Haddow, Pauline C.; Tyrrell, Andy M.

Pages: 3 –37

[The ability of the processes in Nature to achieve remarkable examples of complexity, resilience, inventive solutions and beauty is phenomenal. This ability has promoted engineers and scientists to look to Nature for inspiration. Evolvable Hardware (EH) is one such form of inspiration. It is a...
Available

Bridging the Gap Between Evolvable Hardware and Industry Using Cartesian Genetic Programming

Vasicek, Zdenek

Pages: 39 –55

[Advancements in technology developed in the early nineties have enabled researchers to successfully apply techniques of evolutionary computation in various problem domains. As a consequence, a new research direction referred to as evolvable hardware (EHW) focusing on the use of evolutionary...
Available

Designing Digital Systems Using Cartesian Genetic Programming and VHDL

Henson, Benjamin; Walker, James Alfred; Trefzer, Martin A.; Tyrrell, Andy M.

Pages: 57 –86

[This chapter describes the use of biologically inspired Evolutionary Algorithms (EAs) to create designs for implementation on a reconfigurable logic device. Previous work on Evolvable Hardware (EHW) is discussed with a focus on timing problems for digital circuits. An EA is developed that...
Available

Evolution in Nanomaterio: The NASCENCE Project

Broersma, Hajo

Pages: 87 –111

[This chapter describes some of the work carried out by members of the NASCENCE project, an FP7 project sponsored by the European Community. After some historical notes and background material, the chapter explains how nanoscale material systems have been configured to perform computational tasks...
Available

Using Reed-Muller Expansions in the Synthesis and Optimization of Boolean Quantum Circuits

Younes, Ahmed

Pages: 113 –141

[There have been efforts to find an automatic way to create efficient Boolean quantum circuits, because of their wide range of applications. This chapter shows how to build efficient Boolean quantum circuits. A direct synthesis method can be used to implement any Boolean function as a quantum...
Available

Some Remarks on Code Evolution with Genetic Programming

Banzhaf, Wolfgang

Pages: 145 –156

[In this chapter we take a fresh look at the current status of evolving computer code using Genetic Programming methods. The emphasis is not so much on what has been achieved in detail in the past few years, but on the general research direction of code evolution and its ramifications for GP. We...
Available

Cartesian Genetic Programming for Control Engineering

Clarke, Tim

Pages: 157 –173

[Genetic programming has a proven ability to discover novel solutions to engineering problems. The author has worked with Julian F. Miller, together with some undergraduate and postgraduate students, over the last ten or so years in exploring innovation through evolution, using Cartesian Genetic...
Available

Combining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming

Kaufmann, Paul; Platzner, Marco

Pages: 175 –194

[This work investigates the effects of the periodization of local and global multi-objective search algorithms. We rely on a model for periodization and define a multi-objective evolutionary algorithm adopting concepts from Evolutionary Strategies and NSGAII. We show that our method excels for...
Available

Approximate Computing: An Old Job for Cartesian Genetic Programming?

Sekanina, Lukas

Pages: 195 –212

[Miller’s Cartesian genetic programming (CGP) has significantly influenced the development of evolutionary circuit design and evolvable hardware. We present key ingredients of CGP with respect to the efficient search in the space of digital circuits. We then show that approximate computing, which...
Available

Breaking the Stereotypical Dogma of Artificial Neural Networks with Cartesian Genetic Programming

Khan, Gul Muhammad; Ahmad, Arbab Masood

Pages: 213 –233

[This chapter presents the work done in the field of Cartesian Genetic Programming evolved Artificial Neural Networks (CGPANN). Three types of CGPANN are presented, the Feed-forward CGPANN (FFCGPAN), Recurrent CGPANN and the CGPANN that has developmental plasticity, also called Plastic CGPANN or...

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