Inspired by Nature: Essays Presented to Julian F. Miller on the Occasion of his 60th Birthday

Description

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. Front Matter ....Pages i-x Front Matter ....Pages 1-1 Evolvable Hardware Challenges: Past, Present and the Path to a Promising Future (Pauline C. Haddow, Andy M. Tyrrell)....Pages 3-37 Bridging the Gap Between Evolvable Hardware and Industry Using Cartesian Genetic Programming (Zdenek Vasicek)....Pages 39-55 Designing Digital Systems Using Cartesian Genetic Programming and VHDL (Benjamin Henson, James Alfred Walker, Martin A. Trefzer, Andy M. Tyrrell)....Pages 57-86 Evolution in Nanomaterio: The NASCENCE Project (Hajo Broersma)....Pages 87-111 Using Reed-Muller Expansions in the Synthesis and Optimization of Boolean Quantum Circuits (Ahmed Younes)....Pages 113-141 Front Matter ....Pages 143-143 Some Remarks on Code Evolution with Genetic Programming (Wolfgang Banzhaf)....Pages 145-156 Cartesian Genetic Programming for Control Engineering (Tim Clarke)....Pages 157-173 Combining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming (Paul Kaufmann, Marco Platzner)....Pages 175-194 Approximate Computing: An Old Job for Cartesian Genetic Programming? (Lukas Sekanina)....Pages 195-212 Breaking the Stereotypical Dogma of Artificial Neural Networks with Cartesian Genetic Programming (Gul Muhammad Khan, Arbab Masood Ahmad)....Pages 213-233 Multi-step Ahead Forecasting Using Cartesian Genetic Programming (Ivars Dzalbs, Tatiana Kalganova)....Pages 235-246 Medical Applications of Cartesian Genetic Programming (Stephen L. Smith, Michael A. Lones)....Pages 247-266 Front Matter ....Pages 267-267 Chemical Computing Through Simulated Evolution (Larry Bull, Rita Toth, Chris Stone, Ben De Lacy Costello, Andrew Adamatzky)....Pages 269-286 Sub-Symbolic Artificial Chemistries (Penelope Faulkner, Mihail Krastev, Angelika Sebald, Susan Stepney)....Pages 287-322 Discovering Boolean Gates in Slime Mould (Simon Harding, Jan Koutník, Júrgen Schmidhuber, Andrew Adamatzky)....Pages 323-337 Artificial Development (Tüze Kuyucu, Martin A. Trefzer, Andy M. Tyrrell)....Pages 339-356 Computers from Plants We Never Made: Speculations (Andrew Adamatzky, Simon Harding, Victor Erokhin, Richard Mayne, Nina Gizzie, Frantisek Baluška et al.)....Pages 357-387