The third issue of Volume 20 of Genetic Programming and Evolvable Machines is now available for download.
It contains:
A genetic programming framework in the automatic design of combination models for salient object detection
by Marco A. Contreras-Cruz, Diana E. Martinez-Rodriguez, Uriel H. Hernandez-Belmonte & Victor Ayala-Ramirez
Stochastic synthesis of recursive functions made easy with bananas, lenses, envelopes and barbed wire
by Jerry Swan, Krzysztof Krawiec & Zoltan A Kocsis
Local search in speciation-based bloat control for genetic programming
by Perla Juárez-Smith, Leonardo Trujillo, Mario García-Valdez, Francisco Fernández de Vega & Francisco Chávez
GP-based methods for domain adaptation: using brain decoding across subjects as a test-case
by Roberto Santana, Luis Marti & Mengjie Zhang
Evolving autoencoding structures through genetic programming
by Lino Rodriguez-Coayahuitl, Alicia Morales-Reyes & Hugo Jair Escalante
About the GPEMjournal blog
This is the editor's blog for the journal Genetic Programming and Evolvable Machines. The official web site for the journal, maintained by the publisher (Springer) is here. The GPEMjournal blog is authored and maintained by Lee Spector.
Tuesday, September 3, 2019
Wednesday, May 22, 2019
GPEM 20(2) is now available
The second issue of Volume 20 of Genetic Programming and Evolvable Machines is now available for download.
It contains:
On the scalability of evolvable hardware architectures: comparison of systolic array and Cartesian genetic programming
by Javier Mora, Rubén Salvador & Eduardo de la Torre
Vector quantization using the improved differential evolution algorithm for image compression
by Sayan Nag
EvoParsons: design, implementation and preliminary evaluation of evolutionary Parsons puzzle
by A. T. M. Golam Bari, Alessio Gaspar, R. Paul Wiegand, Jennifer L. Albert, Anthony Bucci & Amruth N. Kumar
A multi-level grammar approach to grammar-guided genetic programming: the case of scheduling in heterogeneous networks
by Takfarinas Saber, David Fagan, David Lynch, Stepan Kucera, Holger Claussen & Michael O’Neill
BOOK REVIEW
Hitoshi Iba: Evolutionary approach to machine learning and deep neural networks: neuro-evolution and gene regulatory networks
by Petra Vidnerová
It contains:
On the scalability of evolvable hardware architectures: comparison of systolic array and Cartesian genetic programming
by Javier Mora, Rubén Salvador & Eduardo de la Torre
Vector quantization using the improved differential evolution algorithm for image compression
by Sayan Nag
EvoParsons: design, implementation and preliminary evaluation of evolutionary Parsons puzzle
by A. T. M. Golam Bari, Alessio Gaspar, R. Paul Wiegand, Jennifer L. Albert, Anthony Bucci & Amruth N. Kumar
A multi-level grammar approach to grammar-guided genetic programming: the case of scheduling in heterogeneous networks
by Takfarinas Saber, David Fagan, David Lynch, Stepan Kucera, Holger Claussen & Michael O’Neill
BOOK REVIEW
Hitoshi Iba: Evolutionary approach to machine learning and deep neural networks: neuro-evolution and gene regulatory networks
by Petra Vidnerová
Sunday, March 31, 2019
GPEM 20(1) is now available
The first issue of Volume 20 of Genetic Programming and Evolvable Machines is now available for download.
It contains:
Editorial introduction
by Lee Spector
Acknowledgment to reviewers
by Lee Spector
DENSER: deep evolutionary network structured representation
by Filipe Assunção, Nuno Lourenço, Penousal Machado & Bernardete Ribeiro
Designing automatically a representation for grammatical evolution
by Eric Medvet, Alberto Bartoli, Andrea De Lorenzo & Fabiano Tarlao
A genetic programming approach for delta hedging
by Zheng Yin, Anthony Brabazon, Conall O’Sullivan & Philip A. Hamill
Evolving continuous cellular automata for aesthetic objectives
by Jeff Heaton
LETTER
Automated discovery of test statistics using genetic programming
by Jason H. Moore, Randal S. Olson, Yong Chen & Moshe Sipper
SOFTWARE REVIEW
Software review: DEAP (Distributed Evolutionary Algorithm in Python) library
by Jinhan Kim & Shin Yoo
BOOK REVIEW
Georgios N. Yannakakis and Julian Togelius: Artificial Intelligence and Games
by Pablo García-Sánchez
BOOK REVIEW
Evelyne Lutton, Nathalie Perrot, Alberto Tonda: Evolutionary algorithms for food science and technology
by Kelly Androutsopoulos
It contains:
Editorial introduction
by Lee Spector
Acknowledgment to reviewers
by Lee Spector
DENSER: deep evolutionary network structured representation
by Filipe Assunção, Nuno Lourenço, Penousal Machado & Bernardete Ribeiro
Designing automatically a representation for grammatical evolution
by Eric Medvet, Alberto Bartoli, Andrea De Lorenzo & Fabiano Tarlao
A genetic programming approach for delta hedging
by Zheng Yin, Anthony Brabazon, Conall O’Sullivan & Philip A. Hamill
Evolving continuous cellular automata for aesthetic objectives
by Jeff Heaton
LETTER
Automated discovery of test statistics using genetic programming
by Jason H. Moore, Randal S. Olson, Yong Chen & Moshe Sipper
SOFTWARE REVIEW
Software review: DEAP (Distributed Evolutionary Algorithm in Python) library
by Jinhan Kim & Shin Yoo
BOOK REVIEW
Georgios N. Yannakakis and Julian Togelius: Artificial Intelligence and Games
by Pablo García-Sánchez
BOOK REVIEW
Evelyne Lutton, Nathalie Perrot, Alberto Tonda: Evolutionary algorithms for food science and technology
by Kelly Androutsopoulos
Tuesday, February 12, 2019
Call For Entries: 16th Annual (2019) "Humies" Awards
Quick reminder the Annual "Humies" Awards featuring cash prizes totalling $10000 for Human-Competitive Results will again be held at GECCO-2019.
This year GECCO will be July 13th-17th, 2019 (Saturday - Wednesday) in Prague, Czech Republic see http://gecco-2019.sigevo.org.
Your human competitive entries (multiple entries are allowed) must be submitted by Wednesday 5 June 2019 by email to goodman at msu dot edu Full details of how to enter can be found via http://www.human-competitive.org
Bill
This year GECCO will be July 13th-17th, 2019 (Saturday - Wednesday) in Prague, Czech Republic see http://gecco-2019.sigevo.org.
Your human competitive entries (multiple entries are allowed) must be submitted by Wednesday 5 June 2019 by email to goodman at msu dot edu Full details of how to enter can be found via http://www.human-competitive.org
Bill
Wednesday, January 23, 2019
Deadline extension: special issue on Integrating Numerical Optimization Methods with Genetic Programming
The deadline for submissions for the special issue on "Integrating Numerical Optimization Methods with Genetic Programming" has been extended.
The revised timeline is:
Submission deadline: February 20, 2019
Notification of first review: May 22, 2019
Resubmission: June 19, 2019
Final acceptance notification: August 14, 2019
The revised timeline is:
Submission deadline: February 20, 2019
Notification of first review: May 22, 2019
Resubmission: June 19, 2019
Final acceptance notification: August 14, 2019
Friday, September 14, 2018
GPEM 19(4) is now available
The fourth issue of Volume 19 of Genetic Programming and Evolvable Machines is now available for download.
It contains:
Grammatical evolution as a hyper-heuristic to evolve deterministic real-valued optimization algorithms
by Iztok Fajfar, Árpád Bűrmen & Janez Puhan
Self-adaptive multi-population genetic algorithms for dynamic resource allocation in shared hosting platforms
by Azam Shirali, Javidan Kazemi Kordestani & Mohammad Reza Meybodi
Comparison of semantic-based local search methods for multiobjective genetic programming
by Tiantian Dou & Peter Rockett
BOOK REVIEW
Alain Pétrowski and Sana Ben-Hamida: Evolutionary Algorithms
by Keith Downing
BOOK REVIEW
Kathryn E. Merrick: Computational models of motivation for game-playing agents
by Spyridon Samothrakis
BOOK REVIEW
Ryan J. Urbanowicz and Will N. Browne: Introduction to learning classifier systems
by Analía Amandi
It contains:
Grammatical evolution as a hyper-heuristic to evolve deterministic real-valued optimization algorithms
by Iztok Fajfar, Árpád Bűrmen & Janez Puhan
Self-adaptive multi-population genetic algorithms for dynamic resource allocation in shared hosting platforms
by Azam Shirali, Javidan Kazemi Kordestani & Mohammad Reza Meybodi
Comparison of semantic-based local search methods for multiobjective genetic programming
by Tiantian Dou & Peter Rockett
BOOK REVIEW
Alain Pétrowski and Sana Ben-Hamida: Evolutionary Algorithms
by Keith Downing
BOOK REVIEW
Kathryn E. Merrick: Computational models of motivation for game-playing agents
by Spyridon Samothrakis
BOOK REVIEW
Ryan J. Urbanowicz and Will N. Browne: Introduction to learning classifier systems
by Analía Amandi
GPEM 19(3) is now available
The third issue of Volume 19 of Genetic Programming and Evolvable Machines, a special issue on genetic programming, evolutionary computation and visualization, edited by Nadia Boukhelifa & Evelyne Lutton, is now available for download.
It contains:
Guest editorial: Special issue on genetic programming, evolutionary computation and visualization
by Nadia Boukhelifa & Evelyne Lutton
Visualising the global structure of search landscapes: genetic improvement as a case study
by Nadarajen Veerapen & Gabriela Ochoa
Unveiling evolutionary algorithm representation with DU maps
by Eric Medvet, Marco Virgolin, Mauro Castelli, Peter A. N. Bosman, Ivo Gonçalves & Tea Tušar
Data exploration in evolutionary reconstruction of PET images
by Cameron C. Gray, Shatha F. Al-Maliki & Franck P. Vidal
Visualisation with treemaps and sunbursts in many-objective optimisation
by David J. Walker
VALIS: an evolutionary classification algorithm
by Peter Karpov, Giovanni Squillero & Alberto Tonda
It contains:
Guest editorial: Special issue on genetic programming, evolutionary computation and visualization
by Nadia Boukhelifa & Evelyne Lutton
Visualising the global structure of search landscapes: genetic improvement as a case study
by Nadarajen Veerapen & Gabriela Ochoa
Unveiling evolutionary algorithm representation with DU maps
by Eric Medvet, Marco Virgolin, Mauro Castelli, Peter A. N. Bosman, Ivo Gonçalves & Tea Tušar
Data exploration in evolutionary reconstruction of PET images
by Cameron C. Gray, Shatha F. Al-Maliki & Franck P. Vidal
Visualisation with treemaps and sunbursts in many-objective optimisation
by David J. Walker
VALIS: an evolutionary classification algorithm
by Peter Karpov, Giovanni Squillero & Alberto Tonda
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