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Introduction

  • Lee SpectorEmail author
Editorial
  • 750 Downloads

Welcome to Volume 14 of Genetic Programming and Evolvable Machines.

In Volume 13 we published a special issue on selected papers from the European conference on genetic programming (thanks to Sara Silva and James A. Foster), an issue containing a special section on evolutionary algorithms for data mining (thanks to Pierre Collet and Man Leung Wong), and two regular issues. Overall Volume 13 presented fifteen research articles, four book reviews, one software review, and three editorials.

This past year also saw the renewal and expansion of the Genetic Programming and Evolvable Machines editorial board. Among the most visible changes are the appointments of three Associate Editors to “Area Editor” positions; these editors retain their status and duties as Associate Editors but they also have new responsibilities related to the shepherding of papers in their areas. As of this writing we have three Area Editors:
  • Area Editor for Life Sciences: James A. Foster, University of Idaho, USA

  • Area Editor for Data Analytics and Knowledge Discovery: Una-May O’Reilly, Massachusetts Institute of Technology, USA

  • Area Editor for Games: Moshe Sipper, Ben-Gurion University, Israel

Among other benefits, we hope to use Area Editors to facilitate interactions with conference organizers and to help researchers transition the field’s best new work from conferences to journal publication.

I am also happy to report the appointment of three new Associate Editors:
  • Terence Soule, University of Idaho, USA

  • Andy Tyrrell, University of York, UK

  • Leonardo Vanneschi, ISEGI, Universidade Nova de Lisboa, Portugal

The complete, expanded editorial board is listed on the journal’s web page. Any additional changes will be posted to the web page and also announced on the editor’s blog at http://gpemjournal.blogspot.com/.

Among the things to which readers can look forward in Volume 14 are a special issue on Evolvability and Robustness in Artificial Evolving Systems (thanks to Lee Altenberg), a special issue on Evolutionary Computation in Art, Sound and Music (thanks to Penousal Machad and Juan Jesús Romero Cardalda), and, if all goes according to plan, the results of an experiment with a new form of peer commentary and discussion related to a target article.

In the present issue we present a methodological article, three research and application articles, and two book reviews. I would like to draw readers’ attention particularly to the methodological article: “Better GP Benchmarks: Community Survey Results and Proposals,” by David R. White, James McDermott, Mauro Castelli, Luca Manzoni, Brian W. Goldman, Gabriel Kronberger, Wojciech Jaśkowski, Una-May OReilly, and Sean Luke. This paper presents the results of a community survey regarding genetic programming benchmark practices and discusses the possible implications of those results. Whether one agrees or disagrees with the perspectives expressed by the authors, or even if one thinks that the authors are asking entirely the wrong questions, I think that this is an important conversation for the research community to be having at the present point in its development.

The other three articles in this issue are “Locally geometric semantic crossover: a study on the roles of semantics and homology in recombination operators” by Krzysztof Krawiec and Tomasz Pawlak, “A comparison of grammatical genetic programming grammars for controlling femtocell network coverage” by Erik Hemberg, Lester Ho, Michael ONeill and Holger Claussen, and “Multi-objective optimization of QCA circuits with multiple outputs using genetic programming” by Razieh Rezaee, Mahboobeh Houshmand and Monireh Houshmand. The book reviews—solicited and edited, as always, by William B. Langdon—are Dario Landa-Silva’s review of Franz Rothlauf’s Design of Modern Heuristics and Vincenzo Bonifaci’s review of Andrew Adamatzky’s Physarum Machines: Computers from Slime Mould.

I hope that you enjoy the present issue and all of Volume 14 of Genetic Programming and Evolvable Machines.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.School of Cognitive ScienceHampshire CollegeAmherstUSA

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