23 submissions to special issue

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!

Search related journals

You can use the following forms to search for text in GPEM-related journals via Google Scholar. Google Scholar doesn't make it easy to do this perfectly, so I have employed some tricks and you still may get some false hits. This should nonetheless be useful in helping you to find and cite related work.

Artificial Life
BioSystems
Complex Systems
Evolutionary Computation
Genetic Prog. and Evol. Mach.
IEEE Trans. on Evol. Comp.
J. Machine Learning Research
Machine Learning

Origins of life research and evolutionary computing

A considerable amount of research in genetic and evolutionary computing is concerned to some degree with self-adaptation -- that is, with the adaptation and improvement of an evolutionary system over evolutionary time. (Try searching for "self-adaptive" in the GPEM journal search and GP-bibliography search boxes on the left.) This work connects not only to research in evolutionary biology but also to research on the origins of life, since it is concerned with the ways in which adaptive systems can themselves arise and become more adaptive.

In this context it is interesting to see today's announcement of an apparent breakthrough in origins of life research, on a possible scenario for the emergence of RNA on prebiotic Earth. This is work by Matthew W. Powner, Beatrice Gerland, and John D. Sutherland at the University of Manchester. There's a write-up in the New York Times, and the full report and a commentary by Jack W. Szostak are available in today's Nature (subscription required for full text).

Among the reasons this might interest GPEM readers is the fact that the discovery was made through an intensive search of the space of chemical reaction sequences. This may be a search space within which genetic and evolutionary computation can help to find new and interesting things, if the right kinds of computational chemistry simulation systems (of which there are many) can be used for fitness testing on with the right kinds of problems. Putting all of this together to make significant discoveries will be non-trivial, but it seems to me to have potential.

Incidentally, searching for "origins" or "chemistry" in the journal, using the top search box on the left, produces several items of related interest that were published previously in GPEM.

CFP: Tenth Anniversary Special Issue on Progress in Genetic Programming and Evolvable Machines

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 Genie in the Machine: How Computer-Automated Inventing is Revolutionizing Law and Buisness

Robert Plotkin has just published a new book for general readers on computer-automated invention and its legal and business implications. I haven't yet read it all the way through but I see that it focuses quite heavily on invention by means of genetic and evolutionary computation. The author consulted with many researchers in developing the ideas -- including myself and several other GPEM editors and authors, listed in the acknowledgments -- so I think that he is well informed about the underlying science and engineering.

The book is The Genie in the Machine: How Computer-Automated Inventing is Revolutionizing Law and Business, published by Stanford University Press, May 2009, ISBN 978-0804756990.