We have just completed the “renewal” process for the Genetic Programming and Evolvable Machines editorial board, the most exciting aspect of which is that we now have a new Associate Editor, Pauline C. Haddow (of The Norwegian University of Science and Technology, Norway) and four new regular members of the editorial board: Marc Ebner (of Eberhard Karls Universität Tübingen, Germany), Jason H. Moore (of Dartmouth Medical School, USA), Sara Silva (of Universidade de Coimbra, Portugal), and Tina Yu (of Memorial University of Newfoundland, Canada). Thanks to all of the continuing associate editors for helping with this process, and welcome to the new editors! I think that the journal will be even stronger with these additions.
The full editorial board can be found
here.
We have just completed the “renewal” process for the Genetic Programming and Evolvable Machines editorial board, the most exciting aspect of which is that we now have a new Associate Editor, Pauline C. Haddow (of The Norwegian University of Science and Technology, Norway) and four new regular members of the editorial board: Marc Ebner (of Eberhard Karls Universität Tübingen, Germany), Jason H. Moore (of Dartmouth Medical School, USA), Sara Silva (of Universidade de Coimbra, Portugal), and Tina Yu (of Memorial University of Newfoundland, Canada). Thanks to all of the continuing associate editors for helping with this process, and welcome to the new editors! I think that the journal will be even stronger with these additions.
The full editorial board can be found
here.
We received 23 submissions to the Special Issue on Parallel and Distributed Evolutionary Algorithms. This is a very healthy number, indicating strong interest in the area and good prospects for an exciting special issue. Congratulations to guest editors Marco Tomassini and Leonardo Vanneschi, thanks to all of the submitters, and thanks in advance to all of the reviewers!
We received 23 submissions to the Special Issue on Parallel and Distributed Evolutionary Algorithms. This is a very healthy number, indicating strong interest in the area and good prospects for an exciting special issue. Congratulations to guest editors Marco Tomassini and Leonardo Vanneschi, thanks to all of the submitters, and thanks in advance to all of the reviewers!
Genetic Programming and Evolvable Machines
Tenth Anniversary Special Issue on Progress in Genetic Programming and Evolvable Machines
(Revised May 19, 2009; please note revised title and deadlines. 2nd revision July 15, 2009. 3rd revision September 25, 2009; please note revised schedule)
Genetic Programming and Evolvable Machines is ten years old in 2010. To mark this, a prestigious special issue of the journal will be published. A number of articles by leading figures have already been commissioned:
- “Theoretical Results in Genetic Programming: The next ten years?” by Riccardo Poli, William B. Langdon, Nic McPhee and Leonardo Vanneschi
- “Human Competitive Results Using Genetic Programming” by John Koza
- “Genetic Programming and Evolvable Machines: Ten Years of Reviews” by William B. Langdon and Steven Gustafson
Open submissions
We encourage the submission of high quality papers that review or analyze progress in the field, present the state-of-the-art in the evolution of software and hardware, describe promising new approaches or application areas, or foundational topics in genetic programming and evolvable machines.
Subjects include, but are not limited to:
– Theoretical understanding of Genetic Programming
– Important Application Areas of Genetic Programming and Evolvable Machines
– New approaches and paradigms
– Fundamental Issues
– Wide ranging reviews and/or analysis of Research in Genetic and Evolvable Machines
Important Dates
– Paper submission deadline: November 23, 2009
– Notification of acceptance: January 15, 2009
– Final manuscript: February 15, 2010
Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by, other journals.All open submissions will be peer reviewed subject to the standards of the journal. Manuscripts based on previously published conference papers must be extended substantially.
Springer offers authors, editors and reviewers of Genetic Programming and Evolvable Machines a web-enabled online manuscript submission and review system. Our online system offers authors the ability to track the review process of their manuscript.
Manuscripts should be submitted to: http://GENP.edmgr.com. This online system offers easy and straightforward log-in and submission procedures, and supports a wide range of submission file formats.
All enquiries on this special issue by prospective authors should be sent to the guest editors at the addresses below.
Guest editors
Julian Miller
Department of Electronics
University of York,
Heslington, York,
YO10 5DD, UK
jfm7@ohm.york.ac.uk
Riccardo Poli
School of Computer Science and Electronic Engineering,
University of Essex,
Wivenhoe Park, Colchester,
CO4 3SQ, UK
rpoli@essex.ac.uk
Editor-in-Chief: Lee Spector, Hampshire College
Founding Editor: Wolfgang Banzhaf, Memorial University of Newfoundland
Journal Website: www.springer.com/10710
Genetic Programming and Evolvable Machines
Tenth Anniversary Special Issue on Progress in Genetic Programming and Evolvable Machines
(Revised May 19, 2009; please note revised title and deadlines. 2nd revision July 15, 2009. 3rd revision September 25, 2009; please note revised schedule)
Genetic Programming and Evolvable Machines is ten years old in 2010. To mark this, a prestigious special issue of the journal will be published. A number of articles by leading figures have already been commissioned:
- “Theoretical Results in Genetic Programming: The next ten years?” by Riccardo Poli, William B. Langdon, Nic McPhee and Leonardo Vanneschi
- “Human Competitive Results Using Genetic Programming” by John Koza
- “Genetic Programming and Evolvable Machines: Ten Years of Reviews” by William B. Langdon and Steven Gustafson
Open submissions
We encourage the submission of high quality papers that review or analyze progress in the field, present the state-of-the-art in the evolution of software and hardware, describe promising new approaches or application areas, or foundational topics in genetic programming and evolvable machines.
Subjects include, but are not limited to:
– Theoretical understanding of Genetic Programming
– Important Application Areas of Genetic Programming and Evolvable Machines
– New approaches and paradigms
– Fundamental Issues
– Wide ranging reviews and/or analysis of Research in Genetic and Evolvable Machines
Important Dates
– Paper submission deadline: November 23, 2009
– Notification of acceptance: January 15, 2009
– Final manuscript: February 15, 2010
Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by, other journals.All open submissions will be peer reviewed subject to the standards of the journal. Manuscripts based on previously published conference papers must be extended substantially.
Springer offers authors, editors and reviewers of Genetic Programming and Evolvable Machines a web-enabled online manuscript submission and review system. Our online system offers authors the ability to track the review process of their manuscript.
Manuscripts should be submitted to: http://GENP.edmgr.com. This online system offers easy and straightforward log-in and submission procedures, and supports a wide range of submission file formats.
All enquiries on this special issue by prospective authors should be sent to the guest editors at the addresses below.
Guest editors
Julian Miller
Department of Electronics
University of York,
Heslington, York,
YO10 5DD, UK
jfm7@ohm.york.ac.uk
Riccardo Poli
School of Computer Science and Electronic Engineering,
University of Essex,
Wivenhoe Park, Colchester,
CO4 3SQ, UK
rpoli@essex.ac.uk
Editor-in-Chief: Lee Spector, Hampshire College
Founding Editor: Wolfgang
Banzhaf, Memorial University of Newfoundland
Journal Website: www.springer.com/10710
The deadline for submitting papers to the Genetic Programming and Evolvable Machines Special Issue on Parallel and Distributed Evolutionary Algorithms has been extended.
The new deadline is: May 15, 2009
More information about the special issue is available here.
The deadline for submitting papers to the Genetic Programming and Evolvable Machines Special Issue on Parallel and Distributed Evolutionary Algorithms has been extended.
The new deadline is: May 15, 2009
More information about the special issue is available here.
The second issue of volume 10 of Genetic Programming and Evolvable Machines is now available online, containing the following articles:
Incorporating characteristics of human creativity into an evolutionary art algorithm
by Steve DiPaola, Liane Gabora
Using enhanced genetic programming techniques for evolving classifiers in the context of medical diagnosis
by Stephan M. Winkler, Michael Affenzeller, Stefan Wagner
Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories
by Sara Silva, Ernesto Costa
A review of procedures to evolve quantum algorithms
by Adrian Gepp, Phil Stocks
Book Review: Riccardo Poli, William B. Langdon, Nicholas F. McPhee: A Field Guide to Genetic Programming
by Michael O’Neill
The second issue of volume 10 of Genetic Programming and Evolvable Machines is now available online, containing the following articles:
Incorporating characteristics of human creativity into an evolutionary art algorithm
by Steve DiPaola, Liane Gabora
Using enhanced genetic programming techniques for evolving classifiers in the context of medical diagnosis
by Stephan M. Winkler, Michael Affenzeller, Stefan Wagner
Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories
by Sara Silva, Ernesto Costa
A review of procedures to evolve quantum algorithms
by Adrian Gepp, Phil Stocks
Book Review: Riccardo Poli, William B. Langdon, Nicholas F. McPhee: A Field Guide to Genetic Programming
by Michael O’Neill
My hardcopy arrived in my mailbox today and it looks good! If you have a subscription yours should arrive soon.
My hardcopy arrived in my mailbox today and it looks good! If you have a subscription yours should arrive soon.
It is easy to sign up for the GPEM “Table of Contents Alert” service, which will send you an email whenever a new issue is published, listing the table of contents for the issue. Just go to Springer’s GPEM page and type your email address in the “Table of Contents Alert” section on the right side of the page.
It is easy to sign up for the GPEM “Table of Contents Alert” service, which will send you an email whenever a new issue is published, listing the table of contents for the issue. Just go to Springer’s GPEM page and type your email address in the “Table of Contents Alert” section on the right side of the page.
From the Introduction to Volume 10, Number 1:
The present issue includes three full research articles and two book reviews.
In “Scaling of Program Functionality” W. B. Langdon provides a novel theoretical analysis of the relations between size and functionality for several classes of programs. Many aspects of his analysis apply to all possible systems that search for computer programs, but Dr. Langdon also describes specific implications of his analysis for genetic programming and provides experimental confirmation of his results.
In “An improved representation for evolving programs” M. S. Withall, C.J. Hinde, and R. G. Stone describe a new representation for evolving programs that combines features of traditional linear and tree-based representations. They present the results of several experiments using their new representation and they discuss implications for the scalability of genetic programming to more complex problems.
In “Solution of matrix Riccati differential equation for nonlinear singular system using genetic programming” P. Balasubramaniam and A. Vincent Antony Kumar show how genetic programming can be used to solve differential equations of a particular important class. They compare the genetic programming approach to the traditional Runge Kutta method and they provide experimental confirmation of efficiency improvements.
The book reviews in this issue, edited by W. B. Langdon, cover two edited volumes: The Mechanical Mind in History, which was edited by P. Husbands, O. Holland and M. Wheeler (reviewed by P. Collet), and Evolutionary Computation in Practice: Studies in Computational Intelligence, which was edited by T. Yu, D. Davis, C. Baydar, and R. Roy (reviewed by L. M. Deschaine).
From the Introduction to Volume 10, Number 1:
The present issue includes three full research articles and two book reviews.
In “Scaling of Program Functionality” W. B. Langdon provides a novel theoretical analysis of the relations between size and functionality for several classes of programs. Many aspects of his analysis apply to all possible systems that search for computer programs, but Dr. Langdon also describes specific implications of his analysis for genetic programming and provides experimental confirmation of his results.
In “An improved representation for evolving programs” M. S. Withall, C.J. Hinde, and R. G. Stone describe a new representation for evolving programs that combines features of traditional linear and tree-based representations. They present the results of several experiments using their new representation and they discuss implications for the scalability of genetic programming to more complex problems.
In “Solution of matrix Riccati differential equation for nonlinear singular system using genetic programming” P. Balasubramaniam and A. Vincent Antony Kumar show how genetic programming can be used to solve differential equations of a particular important class. They compare the genetic programming approach to the traditional Runge Kutta method and they provide experimental confirmation of efficiency improvements.
The book reviews in this issue, edited by W. B. Langdon, cover two edited volumes: The Mechanical Mind in History, which was edited by P. Husbands, O. Holland and M. Wheeler (reviewed by P. Collet), and Evolutionary Computation in Practice: Studies in Computational Intelligence, which was edited by T. Yu, D. Davis, C. Baydar, and R. Roy (reviewed by L. M. Deschaine).
