Inspired by Nature

1. Front Matter

   Pages i-x

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2. Evolution and Hardware

   1. Front Matter

      Pages 1-1

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

      • Pauline C. Haddow, Andy M. Tyrrell

      Pages 3-37

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

      • Zdenek Vasicek

      Pages 39-55

   4. Designing Digital Systems Using Cartesian Genetic Programming and VHDL

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

      Pages 57-86

   5. Evolution in Nanomaterio: The NASCENCE Project

      • Hajo Broersma

      Pages 87-111

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

      • Ahmed Younes

      Pages 113-141

3. Cartesian Genetic Programming Applications

   1. Front Matter

      Pages 143-143

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   2. Some Remarks on Code Evolution with Genetic Programming

      • Wolfgang Banzhaf

      Pages 145-156

   3. Cartesian Genetic Programming for Control Engineering

      • Tim Clarke

      Pages 157-173

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

      • Paul Kaufmann, Marco Platzner

      Pages 175-194

   5. Approximate Computing: An Old Job for Cartesian Genetic Programming?

      • Lukas Sekanina

      Pages 195-212

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

      • Gul Muhammad Khan, Arbab Masood Ahmad

      Pages 213-233

   7. Multi-step Ahead Forecasting Using Cartesian Genetic Programming

      • Ivars Dzalbs, Tatiana Kalganova

      Pages 235-246

   8. Medical Applications of Cartesian Genetic Programming

      • Stephen L. Smith, Michael A. Lones

      Pages 247-266

4. Chemistry and Development

   1. Front Matter

      Pages 267-267

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   2. Chemical Computing Through Simulated Evolution

      • Larry Bull, Rita Toth, Chris Stone, Ben De Lacy Costello, Andrew Adamatzky

      Pages 269-286

   3. Sub-Symbolic Artificial Chemistries

      • Penelope Faulkner, Mihail Krastev, Angelika Sebald, Susan Stepney

      Pages 287-322

   4. Discovering Boolean Gates in Slime Mould

      • Simon Harding, Jan Koutník, Júrgen Schmidhuber, Andrew Adamatzky

      Pages 323-337

   5. Artificial Development

      • Tüze Kuyucu, Martin A. Trefzer, Andy M. Tyrrell

      Pages 339-356

This book is a tribute to Julian Francis Miller’s ideas and achievements in computer science, evolutionary algorithms and genetic programming, electronics, unconventional computing, artificial chemistry and theoretical biology. Leading international experts in computing inspired by nature offer their insights into the principles of information processing and optimisation in simulated and experimental living, physical and chemical substrates. Miller invented Cartesian Genetic Programming (CGP) in 1999, from a representation of electronic circuits he devised with Thomson a few years earlier. The book presents a number of CGP’s wide applications, including multi-step ahead forecasting, solving artificial neural networks dogma, approximate computing, medical informatics, control engineering, evolvable hardware, and multi-objective evolutionary optimisations. The book addresses in depth the technique of ‘Evolution in Materio’, a term coined by Miller and Downing, using a range of examples of experimental prototypes of computing in disordered ensembles of graphene nanotubes, slime mould, plants, and reaction diffusion chemical systems. Advances in sub-symbolic artificial chemistries, artificial bio-inspired development, code evolution with genetic programming, and using Reed-Muller expansions in the synthesis of Boolean quantum circuits add a unique flavour to the content. The book is a pleasure to explore for readers from all walks of life, from undergraduate students to university professors, from mathematicians, computer scientists and engineers to chemists and biologists.

• Evolutionary Algorithms
• Genetic Programming
• Unconventional Computing
• Evolution in Materio
• Evolution and Hardware
• complexity

• Department of Computer Science, University of York, York, United Kingdom

  Susan Stepney

• Unconventional Computing Centre, University of the West of England, Bristol, United Kingdom

  Andrew Adamatzky

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