New Book: Bio-Inspired Computing Machines

[Andres Perez-Uribe]

Dear Connectionist,

This is to announce a new book entitled:

"Bio-Inspired Computing Machines 
 Toward Novel Computational Architectures"

Daniel Mange and Marco Tomassini (Eds.)

Presses polytechniques et universitaires romande, Lausanne, Switzerland

http://lslwww.epfl.ch/pages/publications/books/1998_1/
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Originality:

This book is unique for the following reasons: 
     -
        It follows a unified approach to bio-inspiration based on the
        so-called POE model: phylogeny (evolution of species), ontogeny
        (development of individual organisms), and epigenesis (life-time
        learning).
     -
        It is largely self-contained, with an introduction to both
biological
        mechanisms (POE) and digital hardware (digital systems, cellular
        automata).
     -
        It is mainly applied to computer hardware design.

     -
        It is largely self-contained, with an introduction to both
biological
        mechanisms (POE) and digital hardware (digital systems, cellular
        automata).
     -
        It is mainly applied to computer hardware design.


BACK-COVER TEXT

     This volume, written by experts in the field, gives a modern,
rigorous and unified
     presentation of the application of biological concepts to the
design of novel
     computing machines and algorithms.
     While science has as its fundamental goal the understanding of
Nature, the
     engineering disciplines attempt to use this knowledge to the
ultimate benefit of
     Mankind. Over the past few decades this gap has narrowed to some
extent. A
     growing group of scientists has begun engineering artificial worlds
to test and         probe their theories, while engineers have turned to
Nature, seeking inspiration        in its workings to construct novel
systems. 
     The organization of living beings is a powerful source of ideas for
computer
     scientists and engineers. This book studies the construction of
machines and
     algorithms based on natural processes: biological evolution, which
gives rise to
     genetic algorithms, cellular development, which leads to
self-replicating and
     self-repairing machines, and the nervous system in living beings,
which serves as
     the underlying motivation for artificial learning systems, such as
neural               networks.

PUBLIC

     Undergraduate and graduate students, researchers, engineers,
computer scientists,
     and communication specialists.

TABLE OF CONTENTS

        Preface

      1
        An Introduction to Bio-Inspired Machines
      2
        An Introduction to Digital Systems
      3
        An Introduction to Cellular Automata
      4
        Evolutionary Algorithms and their Applications
      5
        Programming Cellular Machines by Cellular Programming
      6
        Multiplexer-Based Cells
      7
        Demultiplexer-Based Cells
      8
        Binary Decision Machine-Based Cells
      9
        Self-Repairing Molecules and Cells
     10
        L-hardware: Modeling and Implementing Cellular Development using
        L-systems
     11
        Artificial Neural Networks: Algorithms and Hardware
Implementation
     12
        Evolution and Learning in Autonomous Robotic Agents

        Bibliography
        Index 

-- 
Andres PEREZ-URIBE
Logic Systems Laboratory
Computer Science Department
Swiss Federal Institute of Technology-Lausanne
1015 Lausanne, Switzerland
Email: aperez at lslsun.epfl.ch
http://lslwww.epfl.ch/~aperez
Tel: +41-21-693-2652
Fax: +41-21-693 3705