GPEM 12(3) [SI: Evolvable Hardware Challenges] now available online

The third issue of volume 12 of Genetic Programming and Evolvable Machines is now available online, with articles listed below. This is a big and exciting one, the special issue on Evolvable Hardware Challenges, edited by Pauline Haddow. Note also that the introduction and two of the other articles are available for free under open access.

"Introduction: special issue on evolvable hardware challenges"

by Pauline C. Haddow

"Challenges of evolvable hardware: past, present and the path to a promising future"

by Pauline C. Haddow & Andy M. Tyrrell

"An evolved anti-jamming adaptive beamforming network"

by Jason D. Lohn, Jonathan M. Becker & Derek S. Linden

"The evolution of standard cell libraries for future technology nodes"

by James Alfred Walker, James A. Hilder, Dave Reid, Asen Asenov, Scott Roy, Campbell Millar & Andy M. Tyrrell

"Hardware spiking neural network prototyping and application"

by Seamus Cawley, Fearghal Morgan, Brian McGinley, Sandeep Pande, Liam McDaid, Snaider Carrillo & Jim Harkin

"The route to a defect tolerant LUT through artificial evolution"

by Asbjoern Djupdal & Pauline C. Haddow

"Formal verification of candidate solutions for post-synthesis evolutionary optimization in evolvable hardware"

by Zdenek Vasicek & Lukas Sekanina

Software Review: "Open BEAGLE: a generic framework for evolutionary computations"

by Dmitry Batenkov

Book Review: "Sean Luke: essentials of metaheuristics"

by Michael Lones

GPEM 12(2) now available online

The second issue of volume 12 of Genetic Programming and Evolvable Machines is now available online, with the following articles:

"Semantically-based crossover in genetic programming: application to real-valued symbolic regression"

by Nguyen Quang Uy, Nguyen Xuan Hoai, Michael O’Neill, R. I. McKay & Edgar Galván-López

"Have your spaghetti and eat it too: evolutionary algorithmics and post-evolutionary analysis"

by Kfir Wolfson, Shay Zakov, Moshe Sipper & Michal Ziv-Ukelson

"Tracer spectrum: a visualisation method for distributed evolutionary computation"

by Michael O’Neill, Anthony Brabazon & Erik Hemberg

Software Review: "Eureqa: software review"

by Renáta Dubcáková

Book Review: "Hitoshi Iba, Topon Kumar Paul, Yoshohiko Hasegawa: Applied genetic programming and machine learning"

by Kalyan Veeramachaneni

GPEM 12(1) now available online

The first issue of volume 12 of Genetic Programming and Evolvable Machines is now available online, with the following articles:

"Editorial introduction"

by Lee Spector

"Acknowledgement"

by Lee Spector

"Expert-driven genetic algorithms for simulating evaluation functions"

by Omid David-Tabibi, Moshe Koppel & Nathan S. Netanyahu

"Autonomous experimental design optimization of a flapping wing"

by Markus Olhofer, Dilyana Yankulova & Bernhard Sendhoff

"Redundancies in linear GP, canonical transformation, and its exploitation: a demonstration on image feature synthesis"

by Ukrit Watchareeruetai, Yoshinori Takeuchi, Tetsuya Matsumoto, Hiroaki Kudo & Noboru Ohnishi

Book Review: "Justin Lee: Morphogenetic Evolvable Hardware"

by Martin A. Trefzer

Book Review: "Gisele L. Pappa, Alex Freitas: Automating the design of data mining algorithms, an evolutionary computation approach"

by John Woodward

Book Review: "Arthur K. Kordon: Applying computational intelligence: how to create value"

by Guillermo Leguizamón

"Erratum to: Stochastic optimization of a biologically plausible spino-neuromuscular system model"

by Stanley Gotshall, Kathy Browder, Jessica Sampson, Terence Soule & Richard Wells

"Erratum to: Dario Floreano and Claudio Mattiussi: Bio-inspired artificial intelligence: theories, methods, and technologies"

by Ivan Garibay

GPEM 11(2) now available online

The second issue of volume 11 of Genetic Programming and Evolvable Machines is now available online. This is Part 2 of the special issue on parallel and distributed evolutionary algorithms, and it contains the following articles:

"Guest editorial: special issue on parallel and distributed evolutionary algorithms, part two"

by Marco Tomassini and Leonardo Vanneschi

"An ensemble-based evolutionary framework for coping with distributed intrusion detection"

by Gianluigi Folino, Clara Pizzuti and Giandomenico Spezzano

"Deployment of parallel linear genetic programming using GPUs on PC and video game console platforms"

by Garnett Wilson and Wolfgang Banzhaf

"Simdist: a distribution system for easy parallelization of evolutionary computation"

by Boye Annfelt Høverstad

"Variable population size and evolution acceleration: a case study with a parallel evolutionary algorithm"

by Ting Hu, Simon Harding and Wolfgang Banzhaf

"EvAg: a scalable peer-to-peer evolutionary algorithm"

by J. L. J. Laredo, A. E. Eiben, M. van Steen and J. J. Merelo

SIGEVOlution Volume 4, Issue 3, is now available

New issues of the SIGEVOlution newsletter are appearing quite rapidly and the latest---Volume 4 Issue 3---is now available for you to download from: http://www.sigevolution.org

The new issue features:

• Issues in Applying Computational Intelligence by Arthur Kordon
• JavaXCSF by Patrick O. Stalph & Martin V. Butz
• Dissertation corner
• New issues of journals
• Calls & calendar

The newsletter is intended to be viewed electronically.

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

GPEM 11(1) now available online

The first issue of volume 11 of Genetic Programming and Evolvable Machines is now available online, with the following articles:

"Editorial Introduction" and "Acknowledgments" by Lee Spector

"The influence of mutation on population dynamics in multiobjective genetic programming"

by Khaled Badran & Peter I. Rockett

"Automated synthesis of resilient and tamper-evident analog circuits without a single point of failure"

by Vyung-Joong Kim, Adrian Wong & Hod Lipson

"GP challenge: evolving energy function for protein structure prediction" by Pawel Widera, Jonathan M. Garibaldi & Natalio Krasnogor

"The identification and exploitation of dormancy in genetic programming" by David Jackson

"Book Review: Michael Affenzeller, Stefan Wagner, Stephan Winkler and Andreas Beham: Genetic algorithms and genetic programming modern concepts and practical applications" by Gisele L. Pappa

"Book Review: Melanie Mitchell: Complexity a guided tour"

by Felix Streichert

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

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

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

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.

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).