• Publications
  • Influence
Genetic Programming: An Introduction
TLDR
Four appendices summarize valuable resources available for the reader: Appendix A contains printed and recorded resources, Appendix B suggests web-relatedresources, Appendix C discusses GP software tools, including Discipulus, the GP software developed by the authors, and Appendix D mentions events most closely related to the field of genetic programming. Expand
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Artificial Chemistries-A Review
This article reviews the growing body of scientific work in artificial chemistry. First, common motivations and fundamental concepts are introduced. Second, current research activities are discussedExpand
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The “molecular” traveling salesman
  • W. Banzhaf
  • Computer Science
  • Biological Cybernetics
  • 1 October 1990
TLDR
We introduce the concept of isolated evolution to maintain a certain degree of variance in the population of individuals searching in state space defined by the problem. Expand
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Open-Ended Evolution: Perspectives from the OEE Workshop in York
TLDR
We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. Expand
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Open issues in genetic programming
TLDR
We outline some of the challenges and open issues that face researchers and practitioners of Genetic Programming (GP) despite the successful application of GP. Expand
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Genetic Programming of an Algorithmic Chemistry
We introduce a new method of execution for GP-evolved programs consisting of register machine instructions. It is shown that this method can be considered as an artificial chemistry. It lends itselfExpand
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Neural Architecture Transfer
TLDR
Neural architecture search (NAS) has emerged as a promising avenue for automatically designing task-specific neural network architectures that are competitive under multiple conflicting objectives. Expand
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Genetic and Evolutionary Computation – GECCO 2004
TLDR
The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. Expand
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NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search
TLDR
We propose an efficient NAS algorithm for generating task-specific models that are competitive under multiple competing objectives, by adopting explicit surrogate models simultaneously at the upper and the lower level. Expand
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