Category: Evolutionary Intelligence

An interdisciplinary perspective on artificial immune systems

Abstract  This review paper attempts to position the area of Artificial Immune Systems (AIS) in a broader context of interdisciplinary
research. We review AIS based on an established conceptual framework that encapsulates mathematical and co…

Abstract  This review paper attempts to position the area of Artificial Immune Systems (AIS) in a broader context of interdisciplinary
research. We review AIS based on an established conceptual framework that encapsulates mathematical and computational modelling
of immunology, abstraction and then development of engineered systems. We argue that AIS are much more than engineered systems
inspired by the immune system and that there is a great deal for both immunology and engineering to learn from each other
through working in an interdisciplinary manner.

  • Content Type Journal Article
  • DOI 10.1007/s12065-007-0004-2
  • Authors
    • J. Timmis, University of York Department of Computer Science and Department of Electronics Heslington, York YO10 5DD UK
    • P. Andrews, University of York Department of Computer Science Heslington, York YO10 5DD UK
    • N. Owens, University of York Department of Electronics Heslington, York YO10 5DD UK
    • E. Clark, University of York Department of Computer Science Heslington, York YO10 5DD UK

Foreword

Foreword
Content Type Journal ArticleDOI 10.1007/s12065-007-0005-1Authors
Larry Bull, University of the West of England Frenchay Bristol UK

Journal Evolutionary Intelligence Online ISSN 1864-5917Print ISSN 1864-5909

Journal Volume Vo…

Foreword

  • Content Type Journal Article
  • DOI 10.1007/s12065-007-0005-1
  • Authors
    • Larry Bull, University of the West of England Frenchay Bristol UK

Dedication: Dr. Lawrence J. Fogel (1928–2007)

Dedication: Dr. Lawrence J. Fogel (1928–2007)
Content Type Journal ArticleDOI 10.1007/s12065-007-0006-0Authors
Larry Bull, University of the West of England Frenchay Bristol UK

Journal Evolutionary Intelligence Online ISSN 1864-5917Pri…

Dedication: Dr. Lawrence J. Fogel (1928–2007)

  • Content Type Journal Article
  • DOI 10.1007/s12065-007-0006-0
  • Authors
    • Larry Bull, University of the West of England Frenchay Bristol UK

Neuroevolution: from architectures to learning

Abstract  Artificial neural networks (ANNs) are applied to many real-world problems, ranging from pattern classification to robot control.
In order to design a neural network for a particular task, the choice of an architecture (including th…

Abstract  Artificial neural networks (ANNs) are applied to many real-world problems, ranging from pattern classification to robot control.
In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron
model), and the choice of a learning algorithm have to be addressed. Evolutionary search methods can provide an automatic
solution to these problems. New insights in both neuroscience and evolutionary biology have led to the development of increasingly
powerful neuroevolution techniques over the last decade. This paper gives an overview of the most prominent methods for evolving
ANNs with a special focus on recent advances in the synthesis of learning architectures.

  • Content Type Journal Article
  • DOI 10.1007/s12065-007-0002-4
  • Authors
    • Dario Floreano, Ecole Polytechnique Fédérale de Lausanne Laboratory of Intelligent Systems Station 11 1015 Lausanne Switzerland
    • Peter Dürr, Ecole Polytechnique Fédérale de Lausanne Laboratory of Intelligent Systems Station 11 1015 Lausanne Switzerland
    • Claudio Mattiussi, Ecole Polytechnique Fédérale de Lausanne Laboratory of Intelligent Systems Station 11 1015 Lausanne Switzerland