Digital organisms' illuminate evolution
- 19:00 07 May 2003
- NewScientist.com news service
- Will Knight
- Computer programs designed to "evolve" solutions to mathematical problems support the idea that complexity in nature emerges in small, often apparently unremarkable, steps.
Complex biological organisms have long been thought to develop through a series of intermediary evolutionary adaptations, rather than in single giant evolutionary leaps.
Seeing every step along the way in an evolutionary sequence that unfolds over millions of years is of course impossible. But researchers at Michigan State University and the California Institute of Technology in the US have found a way to see this process unfold in its entirety without any 'missing links'.
"Our work allowed us to see how the most complex functions are built up from simpler and simpler functions," says Richard Lenski, a biologist at Michigan State University.
Charles Ofria, a computer scientist at Michigan State University, who was involved with the research, says it may help computer programmers make more efficient evolutionary algorithms.
"One of the beautiful aspects of this work is that it allows us to better understand how nature overcomes difficulties inherent in solving complex problems," he says. "We can then apply these concepts when trying to decide how best to solve computational problems we are faced with."
The researchers created populations of identical "digital organisms", using a computer modeling application called Avida. At the start, each digital organism was incapable of solving logical problems. But with each replication, there was a 20 per cent chance of a random mutation in "offspring". This mutation altered the nature of the digital organism and in some cases resulted in one that could perform a logical operation.
During 15,000 generations or so, the researchers found it was impossible for a population of digital organisms to solve the most difficult logic problems, if that was all that the computer rewarded.
But the outcome changed dramatically if the digital organisms lived in environments that would also reward them if they performed some simpler functions. In that case, the evolving programs were able to bridge the gap and eventually solve even the most complex logic problems.
Evidence of a gradual biological evolutionary process is found in complex structures that retain features related to earlier evolutionary steps. The human eye, for example, contains crystalline proteins that are related to those that perform enzymatic functions unrelated to vision.
The researchers say their computer model will let biologists study individual evolutionary steps for the first time. "Darwinian evolution affects DNA and computer code in much the same way," says Christoph Adami, who leads the Digital Life Laboratory at the California Institute of Technology. "This allows us to study evolution in this electronic medium."
Lenski adds that some mutations, which initially looked as if they would not be advantageous to an organism, turned out to be crucial stepping stones in the long run.