Even More GECCO 2008 HIghlights

David Oranchak has made the best GECCO 2008 coverage I have read so far. See it here.

Some excerpts:

According to Nic McPhee’s twitters, GECCO 2008 had 471 attendees from 46 countries. This universal appeal of scientific research is one of things I liked about last year’s GECCO conference, too. This year’s conference, though, was almost as bad as last year’s when it came to feeding the attendees. Food was given out during the two hour poster session where I was presenting my poster, but all the food was gone in less than 20 minutes, and it was not replenished. Boo!


In the defense applications track, we saw a talk about evolving swarm behaviors for unmanned aerial vehicles (UAVs). Some of the swarming, self-organizing, and attacking behaviors are inspired by behaviors of insects such as bees and wasps. Several interesting micro-UAV technologies were mentioned, such as the Black Widow, UAVs with flapping wings (including bat wings), and parasitic (!!!) UAVs such as SilentEyes (it is launched from larger UAVs). Don’t do anything suspicious, or a swarm of these damned things will form a stinging cloud around you.


There were many more interesting papers, too numerous to describe, showcasing the widespread and diverse applications of evolutionary computing. Some examples include evolving circuits with high testability, automatic defect classification in electronic wafer manufacturing, quantifying quality degradation on voice-over-IP networks, detection of malware (including zero-day virus attacks) using techniques inspired by biological immune systems, evolving color schemes for people with color blindness, investment portfolio optimization, modeling the Milky Way galaxy using BOINC volunteer computing, developing no-loss strategies for tic-tac-toe, finding deadlocks in large concurrent java programs, radar jamming, evolving functions that can detect computer program code plagiarism by students (beware, cheaters!), automatic route planning that takes traffic into consideration, automatic composition of rock music using genetic algorithms (seriously?), interactive evolution of facial composites of suspects in criminal investigations, detection of moving objects in videos, using a bacterial foraging algorithm to detect circles on images (wait, what?), evolving a World Computer Chess Champion-beating chess program by mimicking the behavior of a mentor, and prediction of whether a company will have financial losses.

Excellent coverage!!

Evolving Robot Gait Through Simulated Evolution

Interesting story brought to me via my news webservice:

Students - And Robots - Learn In Professor´s Robotics Lab.

The genetic algorithm applied is the CGA - Cyclic Genetic Algorithm. Not to be confused with the cGA - Compact Genetic Algorithm, an EDA.

The main ideas behind CGA are the following:

Parker made modifications to the standard genetic algorithm to invent the cyclic genetic algorithm (CGA), a method by which cycles of behavior can be learned. The CGA is a method where the computer can self-generate code. In real life, this means that a robot who encounters mud, for instance, might adapt with a different gait. A robot that loses a leg could learn to walk without it.

To demonstrate, Parker changed the parameters on the computer to tell one robot that it was suddenly carrying a heavy load. The robot took on a new walk - slow, deliberate and heavy on stability. In further tests, he showed how the CGA could adapt the robot control codes for partial and full loss of one or two of its legs. "The original CGA method was very limited because it couldn´t react to sensory input," Parker said.

More formaly it can be put as:

"Cyclic Genetic Algorithms were developed to allow for the representation of a cycle of actions in the chromosome. They differ from the standard GA in that the chromosome is in the form of a circle with two tails. The tails of the CGA chromosome are provided to allow for pre and post-cycle procedures. They provide a means for completing tasks before and after entering the cycle. For gait sequence generation, the pre-cycle can position the legs in a ready to walk posture and the post-cycle can return the robot to a stable at rest posture. In our application, we used only the pre-cycle tail. TheCGA genes can be one of several possibilities. They can be as simple as normal genes that represent traits of the individual or they can be as complicated as cyclic sub-chromosomes that can be trained separately by a CGA. For our purposes, the genes represent tasks that are to be completed in a set amount of time. The trained chromosome will contain the cycle of primitive instructions that will be continually repeated by our robot's simple controller to produce a gait.

CGAs can have both fixed and variable length chromosomes. In either case, the system must be able to allot the proper number of tasks to each phase and be flexible enough to allow the CGA to form a complete cycle. When fixed length are used, the tasks at each gene can be repeated. The number of repetitions is encoded in the gene. In this way, fixed length chromosomes can take on the desirable characteristics of variable yet maintain the increased control of training fixed.

More GECCO 2008 Highlights

Martin Pelikan has posted his presentations at GECCO 2008. See it here.

It's a nice overview on estimation of distribution algorithms showed at GECCO this year.

GECCO 2008 Highlights

Nice GECCO 2008 overview from Epistasis blog author Jason Moore, see it here.

Darwinmania

Very interesting articles from New York Times blogger Olivia Judson! In three parts, see them:

Darwinmania!

An Original Confession

Let’s Get Rid of Darwinism

Those articles are intended to celebrate the 150th anniversary of the first announcement of [Darwin's] discovery of natural selection, the main driving force of evolution.

Excellent!!

Evolving Design Through Simulated Evolution

Amazing article from Elisava:

Bionics And Design: Witnesses To The Evolution Of This Approach.

Some quotes from the text:

"[...] Natural history research, even that which seems to be no more than the fruit of pure and empty curiosity, can have very real uses, which would be enough to justify it even to those who only want research into useful things, if before condemning we could have the patience to wait for time to show the use we could make of its [...]."

Rene-Antoine Ferchault de Reaumur, A History of Wasps - 1719.


"It is the story of the development of the branch of mathematics called the calculus of variations, which concerns questions of optimization —finding forms or patterns that maximize or minimize a particular quantity Is the igloo the optimal housing form for minimal heat loss to the outside? Do bees really use the least possible ammount of wax in constructing their hexagonal cells?"

Stefan Hildebrandt & Anthony Tromba - 1985


"The oldest shells in the universe are the crusts of the cooling stars... We can compare them to an egg-shell: they are formed on the surface of moving liquid drops. In long-ago prehistory, about 400 million years ago, living nature took advantage of the fact that a curved structure is 50 to 100 times stronger than a flat structure of the same thickness. This means that the protecting envelope around fragile micro-organisms can as much reduce the expense of material and weight as obtain a greater degree of protection[...]."

Heinz Isler - 1989


"I believe that flowers —vivacious or woody plants— not only present the most frequent type of shell, but that they are also those of the greatest beauty. They offer a complementary perfection: they are kinetic structures. According to need, they can vary their form to open or close the flower, or even to aid the process of pollinization[...]."

Heinz Isler - 1989


"Nature offers us a range of secrets that will not be revealed except with much patience and love [...]."

Le Ricolais - 1935-1969

Darwin And Wallace - 150 Years

Nice overview of the joint presentation held in 1858 - 150 years ago - to show up the first skunks upon evolution through natural selection, see here. The main enthusiasts involved in such a discussion were Charles Darwin and Alfred Russel Wallace. Both of them sent a representative to read their respective writings upon the subject. It's funny to know that the main hall of the famous Linnean Society of London was filled with persons holding a layman skill on evolution and science in general, very different from what a contemporary mind would expect, that is, "experts" following the 19th Century biology Zeitgeist.

It is such important day for evolutionary computation, since in 1858 was the "first generation" of its subsequent development!

I wonder what those two men would say if they saw what their ideas - and others' too - has helped to create and solve...