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

GECCO-2010 competitions announced

The announcement for the GECCO-2010 competitions is out, and it looks good!

GP for self-replication in cellular automata

A new piece on the use of genetic programming for self-replication in cellular automata, by Zhijian Pan and James A. Reggia, has been published in the journal Artificial Life. Previous work on this topic using non-GP genetic algorithms was intriguing, but I always thought that GP could produce even more interesting results. This new article appears to bear that out.

GP (by any name) on RadioLab

Hod Lipson and Michael Schmidt were on the ever-entertaining RadioLab (in the last segment of this show on "Limits"), discussing their remarkable work on "Distilling Free-Form Natural Laws from Experimental Data" that was published in Science last year. Although I don't think they call it GP explicitly in the radio show or even in the main Science article, GP is central to their work, as is explained in detail in the article's Supporting Online Material (links to Science are not free).