GPEM 21(3) is now available

The third issue of Volume 21 of Genetic Programming and Evolvable Machines is now available for download.

This is a special issue on Highlights of Genetic Programming 2019 Events (guest edited by Ting Hu, Miguel Nicolau, and Lukas Sekanina, with associated articles indicated below with "[Highlights]") which also includes a special section on Integrating Numerical Optimization Methods with Genetic Programming (guest edited by Anna I. Esparcia-Alcázar, Leonardo Trujillo, indicated with "[Optimization]").

Contents:

[Highlights]
Guest Editorial
Special issue on highlights of genetic programming 2019 events
Ting Hu, Miguel Nicolau & Lukas Sekanina

[Highlights]
EA-based resynthesis: an efficient tool for optimization of digital circuits
Jitka Kocnova & Zdenek Vasicek

[Highlights]
Horizontal gene transfer for recombining graphs
Timothy Atkinson, Detlef Plump & Susan Stepney

[Highlights]
On the importance of specialists for lexicase selection
Thomas Helmuth, Edward Pantridge & Lee Spector

[Highlights]
A network perspective on genotype–phenotype mapping in genetic programming
Ting Hu, Marco Tomassini & Wolfgang Banzhaf

[Highlights]
Multi-objective genetic programming for manifold learning: balancing quality and dimensionality
Andrew Lensen, Mengjie Zhang & Bing Xue

[Highlights]
Learning feature spaces for regression with genetic programming
William La Cava & Jason H. Moore

[Optimization]
Guest Editorial
Special Issue on Integrating numerical optimization methods with genetic programming
Anna I. Esparcia-Alcázar & Leonardo Trujillo

[Optimization]
Parameter identification for symbolic regression using nonlinear least squares
Michael Kommenda, Bogdan Burlacu, Gabriel Kronberger & Michael Affenzeller

[Optimization]
Unimodal optimization using a genetic-programming-based method with periodic boundary conditions
Rogério C. B. L. Póvoa, Adriano S. Koshiyama, Douglas M. Dias, Patrícia L. Souza & Bruno A. C. Horta

BOOK REVIEW
Arthur I. Miller: The artist in the machine: the world of AI-powered creativity
Anna Olszewska

The Genetic Programming Bibliography: Move and Mirror

The genetic programming bibliography has been successfully moved
and is since summer 2019 has been hosted by the UCL Computer Science department at
http://gpbib.cs.ucl.ac.uk
In the long term there may be other hosting arrangements.

Thanks to Jason H. Moore an automated mirror has been established at
http://gpbib.pmacs.upenn.edu hosted by the University of Pennsylvania,
Penn Medicine Academic Computing Services.  Additional mirrors,
perhaps in the far east, may be established (see daily cron job mirror
script http://gpbib.cs.ucl.ac.uk/tools/gpbib_ucl_mirror.bat ).

The bibliography can be search with google, eg:
earthquake site:gpbib.cs.ucl.ac.uk

Due to the pandemic, regular maintenance, especially additions, has
fallen behind in the last few months.  GP authors are invited to send
new references in BibTex, or to suggest updates, e.g. URLs, or
corrections.

Bill

GPEM 21(1&2) is now available

The first/second issue of Volume 21 of Genetic Programming and Evolvable Machines, a Twentieth Anniversary Special Issue double issue, is now available for download.

It contains:

Editorial introduction
Lee Spector

GP+EM 20th anniversary editorial
Nicholas Freitag McPhee, William B. Langdon

Genetic programming for natural language processing
Lourdes Araujo

Applications of genetic programming to finance and economics: past, present, future
Anthony Brabazon, Michael Kampouridis

Evolutionary music: applying evolutionary computation to the art of creating music
Róisín Loughran, Michael O’Neill

The impact of genetic programming in education
Nelishia Pillay

Genetic programming in the steelmaking industry
Miha Kovačič, Uroš Župerl

Cartesian genetic programming: its status and future
Julian Francis Miller

Genetic programming theory and practice: a fifteen-year trajectory
Moshe Sipper, Jason H. Moore

Genetic programming in the twenty-first century: a bibliometric and content-based analysis from both sides of the fence
Andrea De Lorenzo, Alberto Bartoli

Genetic programming and evolvable machines at 20
W. B. Langdon

Adversarial genetic programming for cyber security: a rising application domain where GP matters
Una-May O’Reilly, Jamal Toutouh

Automatic programming: The open issue?
Michael O’Neill, Lee Spector

BOOK REVIEW
Juan C. Burguillo: Self-organizing coalitions for managing complexity
B. Ombuki-Berman

BOOK REVIEW
Joseph E. Aoun: Robot-proof: higher education at the age of artificial intelligence
Rosa Leonor Ulloa-Cazarez

SOFTWARE REVIEW
Inspyred: Bio-inspired algorithms in Python
Alberto Tonda

SOFTWARE REVIEW
Software review: the GPTIPS platform

Acknowledgment to reviewers (2019)
Lee Spector

GPEM 20(4) is now available

The fourth issue of Volume 20 of Genetic Programming and Evolvable Machines is now available for download.

It contains:

A survey of evolutionary algorithms using metameric representations
by Matt Ryerkerk, Ron Averill, Kalyanmoy Deb & Erik Goodman

A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space
by iet-Hung Dang, Ngo Anh Vien & TaeChoong Chung

A novel multi-swarm particle swarm optimization for feature selection
by Chenye Qiu

A journey among Java neutral program variants
by Nicolas Harrand, Simon Allier, Marcelino Rodriguez-Cancio, Martin Monperrus & Benoit Baudry

GPEM 20(3) is now available

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

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

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