Computer scientists suggest new spin on origins of evolvability

Apr 26, 2013
Associate Professor Kenneth Stanley's current research focuses on artificial intelligence and evolutionary computation. Credit: UCF

Scientists have long observed that species seem to have become increasingly capable of evolving in response to changes in the environment. But computer science researchers now say that the popular explanation of competition to survive in nature may not actually be necessary for evolvability to increase.

In a paper published this week in PLOS ONE, the researchers report that evolvability can increase over generations regardless of whether species are competing for food, habitat or other factors.

Using a simulated model they designed to mimic how organisms evolve, the researchers saw increasing evolvability even without competitive pressure.

"The explanation is that evolvable organisms separate themselves naturally from less evolvable organisms over time simply by becoming increasingly diverse," said Kenneth O. Stanley, an associate professor at the College of Engineering and Computer Science at the University of Central Florida. He co-wrote the paper about the study along with lead author Joel Lehman, a post-doctoral researcher at the University of Texas at Austin.

The finding could have implications for the origins of evolvability in many species.

"When new species appear in the future, they are most likely of those that were evolvable in the past," Lehman said. "The result is that evolvable species accumulate over time even without ."

During the simulations, the team's simulated organisms became more evolvable without any pressure from other organisms out-competing them. The simulations were based on a conceptual algorithm.

"The algorithms used for the simulations are abstractly based on how are evolved, but not on any particular real-life organism," explained Lehman.

The team's is unique and is in contrast to most popular theories for why evolvability increases.

"An important implication of this result is that traditional selective and adaptive explanations for such as increasing evolvability deserve more scrutiny and may turn out unnecessary in some cases," Stanley said.

Stanley is an associate professor at UCF. He has a bachelor's of science in engineering from the University of Pennsylvania and a doctorate in computer science from the University of Texas at Austin. He serves on the editorial boards of several journals. He has over 70 publications in competitive venues and has secured grants worth more than $1 million. His works in artificial intelligence and evolutionary computation have been cited more than 4,000 times.

Lehman has a bachelor's degree in computer science from Ohio State University and a Ph.D. in computer science from UCF. He continues his research at the University of Texas at Austin and is teaching an undergraduate course in artificial intelligence.

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tadchem
not rated yet Apr 26, 2013
"Evolvability" sounds like the 'first derivative' of evolution.
'Unchanging' = static = unable to adapt to changes = doomed to extinction by change.
'Evolution' = changing = able to adapt to change = able to survive change.
'Evolvability' = changeability = ability to adapt to more rapid change.
It is the difference between marginal adaptability and robust adaptability, and it can itself evolve as a result of the *cumulative* effects of the pressures to evolve.
Dug
1 / 5 (3) Apr 26, 2013
"Using a simulated model" and operated by their imaginary friend. GIGO has found perfection in the computer model and all but supplanted basic science and hard data. From climate change to sea level rise computer modeling has been accepted as actual scientific data, rather a theory describing a limited scenario under very specific parameters and whose conclusions change if any one of those parameters change. The natural world is nothing, if it not constant change.
Torbjorn_Larsson_OM
5 / 5 (1) Apr 28, 2013
Nice, it could also be helpful for understanding how the initially communal LUCA population eventually diversified.

@tadchem: Actually it is a capacity, the capacity for adaptation. "Evolvability is the ability of a population of organisms to not merely generate genetic diversity, but to generate _adaptive_ genetic diversity, ..." http://en.wikiped...vability

So it isn't a rate as much as a ratio.

@Dug: It is an oft, so boring, mistaken complaint on science methods.

The article itself shows why it is mistaken, the models here are proposing likely mechanisms to test for (i.e. observe).

This is no different from well tested theories, which are at heart quantifiable models but at the same time the best (set of) scientific data we have. "A theory predicts [is worth] a thousand facts."

Some theories are unlimited, so for example relativity in its prediction of the universal speed limit.

So the GIGO is all yours, great ignorance in = great ignorance out.