Bacteria that turn gears

An interesting inversion of several of the themes covered in this journal:

http://news.yahoo.com/s/livescience/20091226/sc_livescience/scientistsharnessbacteriatoturnmicroscopicgears

It would be even more interesting if gear-turning performance drove selection...

-Lee

SIGEVOlution Volume 4, Issue 1, is now available

The new issue of the SIGEVOlution newsletter, Volume 4 Issue 1, is now available for you to download from: http://www.sigevolution.org

The new issue features:

• "Computational Intelligence Marketing" by Arthur Kordon
• "Pyevolve: a Python Open-Source Framework for Genetic Algorithms" by Christian S. Perone
• Calls & calendar

The newsletter is intended to be viewed electronically.

Thanks to Pier Luca Lanzi, SIGEvolution Editor-in-Chief.

GPEM 10(4) now available online

The fourth issue of volume 10 of Genetic Programming and Evolvable Machines is now available online. This is the first part of the two-part Special Issue on Parallel and Distributed Evolutionary Algorithms, and it contains the following articles:

Introduction: special issue on parallel and distributed evolutionary algorithms, part I

by Marco Tomassini & Leonardo Vanneschi

Distributed differential evolution with explorative–exploitative population families

by Matthieu Weber, Ferrante Neri & Ville Tirronen

A grid-enabled asynchronous metamodel-assisted evolutionary algorithm for aerodynamic optimization

by V. G. Asouti, I. C. Kampolis & K. C. Giannakoglou

Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

by Asim Munawar, Mohamed Wahib, Masaharu Munetomo & Kiyoshi Akama

Parallel evolution using multi-chromosome cartesian genetic programming

by James Alfred Walker, Katharina Völk, Stephen L. Smith & Julian Francis Miller

Genetic programming on graphics processing units

by Denis Robilliard, Virginie Marion-Poty & Cyril Fonlupt

Book Review: Natalio Krasnogor, Steve Gustafson, David A. Pelta, and Jose L. Verdegay (eds): Systems self-assembly: multidisciplinary snapshots

by Navneet Bhalla

Deadline extended for Tenth Anniversary Special Issue on Progress in Genetic Programming and Evolvable Machines

The deadline has been extended for submissions to the Tenth Anniversary Special Issue on Progress in Genetic Programming and Evolvable Machines; see the call for papers for details.

New issue of SIGEVOlution

The new issue of SIGEVOlution is now available for you to download from:

http://www.sigevolution.org

The issue features:

• An Interview with Hans-Paul Schwefel with an introduction by Günter Rudolph
• Memetic Algorithms by Natalio Krasnogor
• Learning From Failures in Evolutionary Computation @ GECCO-2009
• new issues of journals
• calls & calendar

Journal Publication versus Conference Contribution?

In a recent issue of the Communications of the ACM, Moshe Vardi discusses the pros and cons of journal archival publications versus conference contributions. The upshot of his statement, which points to two recent contributions to the viewpoint columns of the journal [1], [2] is that perhaps it is time for Computer Scientists to shift emphasis away from conference and workshop contributions, and start publishing in journal as all other sciences do. A lively discussion followed, see among others, the opinion piece of Lance Fortnow.

As an editor myself of Genetic Programming and Evolvable Machines I have always wondered why it would be more attractive for people in our discipline to publish in conference venues than in archival journals. Are there not enough journals to allow for scientific progress? Or is there a dire need to communicate with colleagues in spatial co-location? Well, to my mind, none of the two! We are not the types of people that wanted to discuss our results to extreme length. Our conferences and workshops usually operate under tight time constraints, and one to three questions is about the average a presenter receives, anything else would eat into the next presenter's time and is discouraged. Also, the number of journals now accepting work from our field has grown over the years to a very reasonable number so that there is no shortage of places where quality work could find a home.

What is it then, that makes us submit and publish so much at conferences? Possible explanations are the existence of deadlines and the incremental nature of much of the work published. The existence of deadlines is a valuable selection pressure in our hectic times where everything is under the dictate of time-driven priorities. It can only be mimicked by journals through the introduction of regular "special issues" which also come with this requirement, and usually are successful in attracting work. As for the second possible explanation, I'd like to cite from [1] on the pitfalls of program committee work: "And arguably it is the more innovative papers that suffer because they are time consuming to read and understand, so they are the most likely to be either completely misunderstood or underappreciated by an increasingly error-prone process." So while innovative work has a harder time at conferences, "our culture creates more units to review with a lower density of new ideas." It is not only that we get to review smaller pieces of work, we are also more busy, with all the workshops and conferences that make us look at these papers. "Genuinely innovative papers that have issues, but could have been conditionally accepted, are all too often rejected in this climate of negativism. So the less ambitious, but well-executed work trumps what could have been the more exciting result." Those would have to be revised and revised and revised again, and there is no time to do this for conferences. Journal articles, on the other hand, can be worked on for a long time, if need be, and there is no time pressure except for the fact that delays could be unbearable and make results obsolete.

In the end, however, it is the impact of the work that counts most. And it is my experience that a carefully edited journal paper is worth the effort, as it produces impact on a scale that conference papers have diffulty to achieve.


[1] K. Birman and F.B. Schneider. Comm. ACM, 52(5) 2009, p. 34
[2] J. Crowcroft, S. Keshav, and N. McKeown, Comm. ACM, 52(1) 2009, p. 27

GPEM 10(3) now available online

The third issue of volume 10 of Genetic Programming and Evolvable Machines is now available online, containing the following articles:

A three-step decomposition method for the evolutionary design of sequential logic circuits

by Houjun Liang, Wenjian Luo and Xufa Wang

Evolutionary design of evolutionary algorithms

by Laura Dioşan and Mihai Oltean

Semantic analysis of program initialisation in genetic programming

by Lawrence Beadle and Colin G. Johnson

Additional awards at GECCO-2009

There were several awards presented at the GECCO-2009 conference aside from the Human-Competitive Results Awards (Humies) awards about which Wolfgang posted previously, and for which I've listed the other winners below. Of particular interest to readers of this blog may be the Best Paper awards from each of the technical tracks; these are generally awarded for exciting new results, several of which may soon be appearing in more complete form in our field's journals. In addition, this year was the first year of the SIGEVO GECCO Impact Award, for the papers with the most citations from the GECCO conference 10 years ago.

Congratulations to all of the winners!

2009 SIGEVO GECCO Impact Awards, for the papers with the most citations from GECCO 1999

M. Pelikan, D. Goldberg, E. Cantu-Paz: "BOA: The Bayesian Optimization Algorithm"

Citations: 447

S. Hofmeyer, S. Forrest: "Immunity by Design: An Artificial Immune System"

Citations: 212

2009 "Humies" Awards for Human-Competitive Results Produced by Genetic and Evolutionary Computation

Humies BRONZE MEDALS

Perez, Olague: "Evolutionary Learning of Local Descriptor Operators for Object Recognition"

AND Hauptpman, Elyasay, Sipper, Karman: "GP to Evolve Solvers for the Rush Hour Problem"

Humies SILVER MEDAL

Shahzad, Zahid, Farooq, Khayam: "GA+PSO for User ID on Smart Phones"

Humies GOLD MEDAL

Forrest, Le Goues, Nguyen, Weimer: "GP for Automated Software Repair"

2009 GECCO Best Paper Awards

Ant Colony Optimization and Swarm Intelligence: "Parallel Shared Memory Strategies for Ant-Based Optimization Algorithms" by T. Bui, T. Nguyen, J. R. Rizzo Jr.

Artificial Life, Evolutionary Robotics, Adaptive Behavior, Evolvable Hardware: "How Novelty Search Escapes the Deceptive Trap of Learning to Learn" by S. Risi, S. D. Vanderbleek, C. E. Hughes, K. O. Stanley

Bioinformatics and Computational Biology Modeling: "Evolutionary Fitness for DNA Motif Discovery" by S. Rahmann, T. Marschall, F. Behler, O. Kramer

Combinatorial Optimization and Metaheuristics: "Fixed-Parameter Evolutionary Algorithms and the Vertex Cover Problem" by S. Kratsch, F. Neumann

Estimation of Distribution Algorithms: "EDA-RL: Estimation of Distribution Algorithms for Reinforcement Learning Problems" by H. Handa

AND

"Approximating the Search Distribution to the Selection Distribution in EDAs" by S. I. Valdez-Peña, A. Hernández-Aguirre, S. Botello-Rionda

Evolution Strategies and Evolutionary Programming: "Efficient Natural Evolution Strategies" by Y. Sun, D. Wierstra, T. Schaul, J. Schmidhuber

Evolutionary Multiobjective Optimization: "Multiplicative Approximations and the Hypervolume Indicator" by T. Friedrich, C. Horoba, F. Neumann

Generative and Developmental Systems: "The Sensitivity of HyperNEAT to Different Geometric Representations of a Problem" by J. Clune, C. Ofria, R. T. Pennock

Genetic Algorithms: "Tunneling Between Optima: Partition Crossover for the Traveling Salesman Problem" by D. Whitley, A. Howe, D. Hains

Genetic Programming: "A Genetic Programming Approach to Automated Software Repair" by S. Forrest, T.V. Nguyen, W. Weimer, C. Le Goues

Genetics-Based Machine Learning: "Learning Sensorimotor Control Structures with XCSF" by M. V. Butz, G. K. M. Pedersen, P. O. Stalph

AND

"New Entropy Model for Extraction of Structural Information from XCS Population" by W. K. Park, J. C. Oh

Parallel Evolutionary Systems: "Strategies to Minimise the Total Run Time of Cyclic Graph Based Genetic Programming with GPUs" by T. E. Lewis, G. D. Magoulas

Real World Applications: "Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm" by F.-M. De Rainville, C. Gagné, O. Teytaud, D. Laurendeau

Search Based Software Engineering: "Software Project Planning for Robustness and Completion Time in the Presence of Uncertainty using Multi Objective Search Based Software Engineering" by S. Gueorguiev, M. Harman, G. Antoniol

Theory: "Dynamic Evolutionary Optimisation: An Analysis of Frequency and Magnitude of Change" by P. Rohlfshagen. P. K. Lehre, X. Yao

GECCO Graduate Student Workshop: "Learnable Evolution Model Performance Impaired by Binary Tournament Survival Selection" by M. Coletti (George Mason University)

GECCO Humies Award (GOLD) 2009

GP was well featured at this year's GECCO Humies Awards. The most spectacular application which was subsequently awarded first prize (GOLD) was based on two papers by Weimer/Nguyen/Le Goues/Forrest
published in proceedings of the 31st International Conference on Software Engineering (ICSE) in May 2009 and Forrest/Weimer/Nguyen/Le Goes in this year's GECCO proceedings. Both papers won awards from the respective conferences, and winning the Humies award was the "icing on the cake".

The authors apply a specialized/improved form of Genetic Programming to locate and repair software bugs. Repairing software bugs is a time consuming and commercially very costly activity. To date, automating the process has been very difficult. The GP method proposed by our Gold Medal winners takes down the average repair time for software bugs from more than 3 hours per bug to 3 minutes.

The authors rightly claim that "showing how to use GP in the context of modern software systems and integrating GP into modern software practice will help evolutionary computation to become more widely accepted by computer scientists."

Congratulations to the authors for a prize well deserved!

Award for David E. Goldberg

David E. Goldberg has been awarded an Evolutionary Computation Pioneer Award by the Computational Intelligence Society. More details here. Well-deserved congratulations to David, who has given so much to our field!

SIGEVOlution Volume 3, Issue 3, is now available

I'm a little late with this post because I couldn't reach the blog from China (where I was for the 2009 World Summit on Genetic and Evolutionary Computation). Aside from the web access issues it was an interesting conference and I had a great visit in China more generally. I'm now in Tokyo where I'll visit GPEM associate editor Hitoshi Iba tomorrow, and the only web challenge appears to be in getting Blogger's menus to appear in English rather than Japanese... but I've managed.

Anyway, in the interim I have received mail from Pier Luca Lanzi informing me that the latest issue of SIGEVOlution, the SIGEVO newsletter, has just been released. It is available from http://www.sigevolution.org and features:

• An Interview with John H. Holland with an introduction by Lashon Booker
• It's Not Junk! by Clare Bates Congdon, H. Rex Gaskins, Gerardo M. Nava & Carolyn Mattingly
• Car racing @ CIG-2008
• GECCO-2009 competitions
• New issues of journals
• Calls & calendar

Don't be confused by the "Autumn 2008" cover date. It is indeed a new issue that just came out in June, 2009, but the volume/date correspondence has slipped (and will probably be adjusted soon).

Editorial board renewed

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.

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.

Deadline extended for Special Issue on Parallel and Distributed Evolutionary Algorithms

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.

Evolution of Modularity, GP, and a new PLoS Computational Biology paper by Kashtan et al.

A new paper by Kashtan et al. in PLoS Computational Biology presents an interesting study of the evolution of modularity, extending their previous work showing "that modular structure can spontaneously emerge if goals (environments) change over time, such that each new goal shares the same set of sub-problems with previous goals."

The evolution of modularity is a topic of longstanding interest in GP and evolutionary computation more generally, within which we often seek to evolve modular programs or structures. Many also seek to leverage the modularity of representations to accelerate evolution. A lot of the work on automatically defined functions, etc., has been concerned with these issues and I think that cross-fertilization with the new computational biology results could be fruitful.

The closest thing that I know of in the GP literature to the Kashtan et al. results is a paper by Terry Van Belle and David Ackley in GECCO 2002, in which they observed the "evolution of evolvability in experiments using genetic programming to solve a symbolic regression problem that varies in a partially unpredictable manner." Alan Robinson and I were inspired by this to do a similar experiment in PushGP, which allows modularity to arise from scratch via code self-manipulation, and we wrote it up briefly in a GECCO 2002 Workshop paper (see section 3.2).

GPEM 10(2) now available online

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

Website for The Art of Artificial Evolution

A nice website has been set up for The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, a book edited by Juan Romero and Penousal Machado that was reviewed by Jeroen Eggermont in GPEM 10(1).

Medical applications as a growth area for genetic and evolutionary computing

Within the last week we've been notified of several new citations to GPEM articles on medical/pharmaceutical applications, which is consistent with my impression that this is a particularly promising growth area for the field.

Our special issue on "Medical Applications of Genetic and Evolutionary Computation" (guest editors Stephen L. Smith and Stefano Cagnoni) was published in December of 2007, and we have published related work both before and after that special issue -- for example we published "Use of genetic programming to diagnose venous thromboembolism in the emergency department" by Milo Engoren and Jeffrey A. Kline in March, 2008, and two relevant articles in September, 2008 ("Genetic programming for medical classification: a program simplification approach" by Mengjie Zhang and Phillip Wong, and "Analysis of mass spectrometry data of cerebral stroke samples: an evolutionary computation approach to resolve and quantify peptide peaks" by Julio J. Valdes, Alan J. Barton, and Arsalan S. Haqqani). Also upcoming and now in Online First: "Using enhanced genetic programming techniques for evolving classifiers in the context of medical diagnosis" by Stephan M. Winkler, Michael Affenzeller and Stefan Wagner.

I think that there's  a lot of potential here both for new applications and for GPEM to bring more of the ongoing work to the broader research community. I would encourage researchers who work in this area to contact me about possibilities.

GPEM 10(1) hits the streets

My hardcopy arrived in my mailbox today and it looks good! If you have a subscription yours should arrive soon.

Evolution of life in 60 seconds

Via seedmagazine.com, a very nice animation of the time scale of biological evolution on Earth. I think it makes its point beautifully, with an aesthetic that echoes Powers of Ten and The Outer Limits. The shape of the underlying curve is probably worth keeping in mind for artificial evolutionary systems as well.

GECCO conference highly ranked

According to the rankings at this site, the Genetic and Evolutionary Computation Conference (GECCO) ranks 11th out of 701 considered conferences in "Artificial Intelligence / Machine Learning / Robotics / Human Computer Interaction." The rankings are based on citation of papers, quality of referees' reports, availability of resources to students by the conference, conference papers accepted/appeared in reputable journals after the conference, and indexing (details here).

CFP: Special Issue on Parallel and Distributed Evolutionary Algorithms

Genetic Programming and Evolvable Machines

Special Issue on Parallel and Distributed Evolutionary Algorithms

(Revised March 27, 2009; please note revised submission procedures.)

(Revised April 29, 2009; extended submission deadline.)

Genetic Programming, and Evolutionary Computation at
large have been extremely successful in the last decade across
a wide range of problems and applications. Current applications are
characterized by an ever growing complexity and a pronounced
distributed nature. While the use of centralized or hierarchical
architectures and algorithms has been dominant so far, they are
now becoming impractical because they have poor scalability and
fault-tolerance characteristics. Since evolutionary algorithms are
ideally suited to population partitioning and structuring, distributed
and parallel approaches appear to be a natural way to
cope with the growing computational burden associated with large
problems.

The aim of this Special Issue is to provide the reader with
contributions discussing recent advances and an indication of
future trends in the theory, development, and application of
parallel and distributed evolutionary algorithms. We encourage
submission of papers describing new concepts, models, and
strategies, along with papers describing systems and tools that
provide practical implementations. Papers describing either
hardware or software aspects of parallel and distributed
architectures are welcome. In addition, we are interested in
application papers discussing the power and applicability of these
parallel methods to real-world problems in any area of interest,
such as evolutionary design, optimization, and emerging fields
such as computational biology.

Subjects will include (but are not limited to):

- parallel and distributed evolutionary algorithms models

- theory of structured evolutionary algorithms

- performance evaluation of parallel and distributed
evolutionary algorithms

- applications of parallel and distributed evolutionary computing

- parallel and distributed implementations: software and
hardware aspects

Important dates:

* Paper submission deadline: May 15, 2009 [extended from April 30, 2009]
* Notification of acceptance: June 30, 2009
* Final manuscript: August 31, 2009

Paper Submission:

Authors are encouraged to submit high-quality, original work

that has neither appeared in, nor is under consideration by, other

journals. All 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 perspective authors should
be sent to the guest editors at the addresses below.

Guest editors:

Marco Tomassini
Information Systems Institute
University of Lausanne, Lausanne, Switzerland
marco.tomassini@unil.ch
Tel: +41 21 6923589

Leonardo Vanneschi
Department of Informatics, Systems and Communication (D.I.S.Co.)
Building U14, Office n. 2004
viale Sarca, 336
University of Milano-Bicocca, Milano, Italy
vanneschi@disco.unimib.it
Tel.: +39 02 64487874

Editor-in-Chief: Lee Spector, Hampshire College
Founding Editor: Wolfgang Banzhaf, Memorial University of Newfoundland
Journal Website: www.springer.com/10710

Evolectronica

Bob MacCallum has rolled out his new evolutionary music website -- using genetic programming and human fitness assessment -- just in time for Darwin's 200th birthday. The interface still isn't 100% smooth (on my mac at least), but it works and it produces some interesting output. Check it out at http://evolectronica.com.

Get GPEM tables of contents by email

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.

Evolutionary computing and boron

Today's New York Times features an article describing a new discovery about the element boron, made in part by evolutionary computing. Full details of the discovery are provided in a January 29, 2009 letter in Nature (subscription required). They (Oganov et al.) used a special purpose evolutionary algorithm called USPEX that is not really described in the Nature piece, but it is described elsewhere including here.

Contents of Volume 10, Number 1

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).