Artificial Life Models in Hardware

  • Andrew Adamatzky
  • Maciej Komosinski

Table of contents

  1. Front Matter
    Pages i-xviii
  2. James M. Conrad, Jonathan W. Mills
    Pages 1-20
  3. Fumiya Iida, Simon Bovet
    Pages 21-33
  4. Toshio Fukuda, Tadayoshi Aoyama, Yasuhisa Hasegawa, Kosuke Sekiyama
    Pages 65-86
  5. Paolo Arena, Sebastiano De Fiore, Luca Patané
    Pages 103-132
  6. Tetsuya Asai, Takahide Oya
    Pages 133-159
  7. Shuhei Miyashita, Max Lungarella, Rolf Pfeifer
    Pages 161-184
  8. Ioannis A. Ieropoulos, John Greenman, Chris Melhuish, Ian Horsfield
    Pages 185-211
  9. Soichiro Tsuda, Stefan Artmann, Klaus-Peter Zauner
    Pages 213-232
  10. Andrew Adamatzky, Benjamin De Lacy Costello, Hiroshi Yokoi
    Pages 233-264
  11. Back Matter
    Pages 265-267

About this book


Hopping, climbing and swimming robots, nano-size neural networks, motorless walkers, slime mould and chemical brains --- this book offers unique designs and prototypes of life-like creatures in conventional hardware and hybrid bio-silicon systems. Ideas and implementations of living phenomena in non-living substrates cast a colourful picture of state-of-the-art advances in hardware models of artificial life.

Focusing on topics and areas based on non-traditional thinking, and new and emerging paradigms in bio-inspired robotics, this book has a unifying theme: the design and real-world implementation of artificial life robotic devices.

Students and researchers will find this coverage of topics such as robotic energy autonomy, multi-locomotion of robots, biologically inspired autonomous robots, evolution in colonies of robotic insects, neuromorphic analog devices, self-configurable robots, and chemical and biological controllers for robots, will considerably enhance their understanding of the issues involved in the development of not-traditional hardware systems at the cusp of artificial life and robotics.


Artificial Life Bioengineering, biomechanics and bioelectronics Evolution Hardware Nature-inspired Robotics Physical Simulation of living forms biologically inspired dynamical systems learning neural network perception robot robotics

Editors and affiliations

  • Andrew Adamatzky
    • 1
  • Maciej Komosinski
    • 2
  1. 1.Department of Computer ScienceUniversity of the West of EnglandBristolUK
  2. 2.Institute of Computing SciencePoznan University of TechnologyPoznanPoland

Bibliographic information

  • DOI
  • Copyright Information Springer London 2009
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-84882-529-1
  • Online ISBN 978-1-84882-530-7
  • Buy this book on publisher's site