Article.

Excerpt: A long-standing challenge to evolutionary theory has been whether it can explain the origin of complex organismal features. We examined this issue using digital organisms—computer programs that self-replicate, mutate, compete and evolve. Populations of digital organisms often evolved the ability to perform complex logic functions requiring the coordinated execution of many genomic instructions. Complex functions evolved by building on simpler functions that had evolved earlier, provided that these were also selectively favoured. However, no particular intermediate stage was essential for evolving complex functions. The first genotypes able to perform complex functions differed from their non-performing parents by only one or two mutations, but differed from the ancestor by many mutations that were also crucial to the new functions. In some cases, mutations that were deleterious when they appeared served as stepping-stones in the evolution of complex features. These findings show how complex functions can originate by random mutation and natural selection.

Excerpt: Artificial Life Experiments Show How Complex Functions Can Evolve

Arlington, Va.—If the evolution of complex organisms were a road trip, then the simple country drives are what get you there. And sometimes even potholes along the way are important.

An interdisciplinary team of scientists at Michigan State University and the California Institute of Technology, with the help of powerful computers, has used a kind of artificial life, or ALife, to create a road map detailing the evolution of complex organisms, an old problem in biology.

In an article in the May 8 issue of the international journal Nature, Richard Lenski, Charles Ofria, Robert Pennock, and Christoph Adami report that the path to complex organisms is paved with a long series of simple functions, each unremarkable if viewed in isolation. "This project addresses a fundamental criticism of the theory of evolution, how complex functions arise from mutation and natural selection," said Sam Scheiner, program director in the division of environmental biology at the National Science Foundation (NSF), which funded the research through its Biocomplexity in the Environment initiative. "These simulations will help direct research on living systems and will provide understanding of the origins of biocomplexity."

Some mutations that cause damage in the short term ultimately become a positive force in the genetic pedigree of a complex organism. "The little things, they definitely count," said Lenski of Michigan State, the paper's lead author. "Our work allowed us to see how the most complex functions are built up from simpler and simpler functions. We also saw that some mutations looked like bad events when they happened, but turned out to be really important for the evolution of the population over a long period of time."

In the key phrase, "a long period of time," lies the magic of ALife. Lenski teamed up with Adami, a scientist at Caltech's Jet Propulsion Laboratory and Ofria, a Michigan State computer scientist, to further explore ALife.

Pennock, a Michigan State philosopher, joined the team to study an artificial world inside a computer, a world in which computer programs take the place of living organisms. These computer programs go forth and multiply, they mutate and they adapt by natural selection.

The program, called Avida, is an artificial petri dish in which organisms not only reproduce, but also perform mathematical calculations to obtain rewards. Their reward is more computer time that they can use for making copies of themselves. Avida randomly adds mutations to the copies, thus spurring natural selection and evolution. The research team watched how these "bugs" adapted and evolved in different environments inside their artificial world.

Avida is the biologist's race car - a really souped up one. To watch the evolution of most living organisms would require thousands of years – without blinking. The digital bugs evolve at lightening speed, and they leave tracks for scientists to study.

"The cool thing is that we can trace the line of descent," Lenski said. "Out of a big population of organisms you can work back to see the pivotal mutations that really mattered during the evolutionary history of the population. The human mind can't sort through so much data, but we developed a tool to find these pivotal events."

There are no missing links with this technology.

Evolutionary theory sometimes struggles to explain the most complex features of organisms. Lenski uses the human eye as an example. It's obviously used for seeing, and it has all sorts of parts - like a lens that can be focused at different distances - that make it well suited for that use. But how did something so complicated as the eye come to be?

Since Charles Darwin, biologists have concluded that such features must have arisen through lots of intermediates and, moreover, that these intermediate structures may once have served different functions from what we see today. The crystalline proteins that make up the lens of the eye, for example, are related to those that serve enzymatic functions unrelated to vision. So, the theory goes, evolution borrowed an existing protein and used it for a new function.

"Over time," Lenski said, "an old structure could be tweaked here and there to improve it for its new function, and that's a lot easier than inventing something entirely new."

That's where ALife sheds light.

"Darwinian evolution is a process that doesn't specify exactly how the evolving information is coded," says Adami, who leads the Digital Life Laboratory at Caltech. "It affects DNA and computer code in much the same way, which allows us to study evolution in this electronic medium."

Many computer scientists and engineers are now using processes based on principles of genetics and evolution to solve complex problems, design working robots, and more. Ofria says that "we can then apply these concepts when trying to decide how best to solve computational problems."

"Evolutionary design," says Pennock, "can often solve problems better than we can using our own intelligence."

post Excerpt: As someone who was actually working on Avida at the time and visited Microsoft Research in Redmond with Charles and Chris (Ofria and Adami respectively). I just thought I'd say a few things.

MS (through the head of University Relations at the time) did give a no-strings-attached gift (and a computer for my desk) because they thought it was neat research. The same head of Univ Relations at MS actually did a great deal of coding on avida to port it to Windows. I don't think they really thought that Alife or GP or GA or AI would be useful in any products anytime in the forseable future, but they did to seem to think it was cool and maybe important someday. I'd also like to point out that MS Research had two theoretical physicists on staff that did theoretical physics (with no obvious connection to any potential products).

We did visit MS Research, and it was way cool. Sat around talking with lots of really smart people about various random ideas. I don't think we really had anything to contribute to their work an at all direct manner, but everyone we spoke with was really smart and seemed pretty interested in Alife. I want to point out a very important observation here since this is /. after all. MS Research is not MS Marketing. The culture, motiviations, and average intellegence levels are way different. Also, at the time, MS Research wasn't under much pressure to do anything useful in the short term. Sadly, I've been told by friends there that this has changed and it has become a much less fun place to work.

About the paper... I didn't write it or even get an opportunity to read it (sniff), but I did chat about it with the authors when it was being worked on, and their intention was to write a paper that showed how "Irreducable Complex Structures" can arise from very basic mutation/selection. The point was to pop the "Intelligent Design" creationists bubble that they seem to have regarding the scientific basis of their claims.

Pennock wrote "Tower of Babel: The Evidence against the New Creationism" and "Intelligent Design Creationism and Its Critics: Philosophical, Theological, and Scientific Perspectives". Lenski is a brilliant Microbiologist (bacteria, viruses, and such). Ofria is a Computer Scientist with a background in Alife (and a friend of mine). Adami's background is from Quantum Physics (where he has made important contributions), but has been one of the stong voices for doing real science using alife (trying to understand how evolution actually works) instead of just making pretty pictures with dots.

IdahoEv post Excerpt: For the record, I'm one of Dr. Adami's grad students in (The Digital Life Lab) at Caltech. Most of the programming is done at our sister lab in Michigan.

We recently released Avida version 2.0, with a new GUI and complete with god mode where you can inspect and edit the genome of any organism at any point.

We encourage you to play with Avida yourself. You can get information and a Mac OS X binary at:

Avida's Hompeage [caltech.edu]. Older versions for linux and windows are available there as well.

The intrepid can build the current version for OS X or Linux from source, please see Avida's Sourceforge Project [sourceforge.net]. If you want the nice GUI, you'll need QT.

Other information about Avida, our lab's research, and artificial life in general can be found at:

The Digital Life Lab Homepage [caltech.edu]

Our sister lab at MSU, run by Professors Charles Ofria [msu.edu] and Richard Lenski [msu.edu].

The Int'l Society For Artificial Life [alife.org]

Dr. Charles A. Ofria post Excerpt: To add one more comment to this (from the Michigan lab mentioned above) we'll have a Windows version of the software out "real soon now". Just this past week we've gotten everything compiled under Visual C++, and are hammering out the last few major bugs. We'll put up a beta as soon as its reasonably solid.