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Inspired by Nature

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Cover of 'Inspired by Nature'

Table of Contents

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    Book Overview
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    Chapter 1 Evolvable Hardware Challenges: Past, Present and the Path to a Promising Future
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    Chapter 2 Bridging the Gap Between Evolvable Hardware and Industry Using Cartesian Genetic Programming
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    Chapter 3 Designing Digital Systems Using Cartesian Genetic Programming and VHDL
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    Chapter 4 Evolution in Nanomaterio: The NASCENCE Project
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    Chapter 5 Using Reed-Muller Expansions in the Synthesis and Optimization of Boolean Quantum Circuits
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    Chapter 6 Some Remarks on Code Evolution with Genetic Programming
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    Chapter 7 Cartesian Genetic Programming for Control Engineering
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    Chapter 8 Combining Local and Global Search: A Multi-objective Evolutionary Algorithm for Cartesian Genetic Programming
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    Chapter 9 Approximate Computing: An Old Job for Cartesian Genetic Programming?
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    Chapter 10 Breaking the Stereotypical Dogma of Artificial Neural Networks with Cartesian Genetic Programming
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    Chapter 11 Multi-step Ahead Forecasting Using Cartesian Genetic Programming
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    Chapter 12 Medical Applications of Cartesian Genetic Programming
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    Chapter 13 Chemical Computing Through Simulated Evolution
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    Chapter 14 Sub-Symbolic Artificial Chemistries
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    Chapter 15 Discovering Boolean Gates in Slime Mould
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    Chapter 16 Artificial Development
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    Chapter 17 Computers from Plants We Never Made: Speculations
Attention for Chapter 17: Computers from Plants We Never Made: Speculations
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Chapter title
Computers from Plants We Never Made: Speculations
Chapter number 17
Book title
Inspired by Nature
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-67997-6_17
Book ISBNs
978-3-31-967996-9, 978-3-31-967997-6
Authors

Andrew Adamatzky, Simon Harding, Victor Erokhin, Richard Mayne, Nina Gizzie, Frantisek Baluška, Stefano Mancuso, Georgios Ch. Sirakoulis

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Luxembourg 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 32%
Student > Ph. D. Student 9 32%
Other 3 11%
Student > Bachelor 3 11%
Student > Doctoral Student 1 4%
Other 2 7%
Unknown 1 4%
Readers by discipline Count As %
Computer Science 6 21%
Engineering 4 14%
Agricultural and Biological Sciences 3 11%
Physics and Astronomy 2 7%
Neuroscience 2 7%
Other 6 21%
Unknown 5 18%