Assumption: We go swoop! from here to there without going through the middle. Not true, small changes and selection for beneficial ones allows us to get very far relatively rapidly.
The researchers set up an experiment to document how one particularly complex operation evolved. The operation, known as equals, consists of comparing pairs of binary numbers, bit by bit, and recording whether each pair of digits is the same. It's a standard operation found in software, but it's not a simple one. The shortest equals program Ofria could write is 19 lines long. The chances that random mutations alone could produce it are about one in a thousand trillion trillion. To test Darwin's idea that complex systems evolve from simpler precursors, the Avida team set up rewards for simpler operations and bigger rewards for more complex ones. The researchers set up an experiment in which organisms replicate for 16,000generations. They then repeated the experiment 50 times.
Avida beat the odds. In 23 of the 50 trials, evolution produced organisms that could carry out the equals operation. And when the researchers took away rewards for simpler operations, the organisms never evolved an equals program. “When we looked at the 23 tests, they were all done in completely different ways,” adds Ofria. He was reminded of how Darwin pointed out that many evolutionary paths can produce the same complex organ. A fly and an octopus can both produce an image with their eyes, but their eyes are dramatically different from ours. “Darwin was right on that-there are many different ways of evolving the same function,” says Ofria.
Check out the story of Avida artificial life here.
Artificial evolution is actually a happening area in programming and circuit design because it can sample many variations very rapidly and end up constructing a system that looks really weird to us, but often works better than what we can manage through "intelligent design."
"Evolutionary algorithms" and related ( and other related algorithms Tabu search, simulated annealing, Boltzman networks etc. ) are actually an interest of mine.
x[t+1] = s( v( x[t]) )
where x[t] is the population under a representation at time t, v(.) is the variation operator(s), and s(.) is the selection operator.
Evolutionary algorithms and genetic programming are actually a subset of a more general type of stochastic method of machine learning. These algorithms are nifty but only if the selection operator and variation operator, and the termination condition are very carefully designed. Every step of the design of an evolutionary algorithm/stochastic learning algorithm requires careful planning and purposeful choices, otherwise nothing useful ever comes out of these algorithms. I know from experience that it is actually easy to write one which will never converge on the optimal set of parameters. These algorithms are often designed to discover a particular design. These algorithms also require a preexisting highly ordered/designed computational device capable of running the same set of designed instructions over and over and over again with out error.
Every "feature" in Avida “digital organism” is a mathematical abstraction of a preexisting design.
Humans discover abstractions and laws which God created in the universe. Creating observed mathematical abstractions and then running them through a stochastic method of machine learning doesn’t show that a plant or an organism is performing an optimization calculation. Avida is an intelligently contrived program from more than a more than a decade of development. One cannot prove that the world as we observed it is a by-product of chaos with an experiment centered on events inside something that owes its very existence to outside interference with nature. The fact remains that Avida and the computer itself owe their very existence to human imposition of order from outside. After more than a decade of development, because of presuppositions that ‘matter is all there is’, the fact that the artificial environment of Avida was 'intelligently designed' is ignored.
An interesting probability model that you may find interesting is calculating the probability of trying to assemble life from non-life purely by chance and natural process:
http://www.freerepublic.com/focus/f-news/1689062/posts?page=185#185
a) Calculations of Sir Fred Hoyle and Chandra Wickramasinghe for random generation of a simple enzyme and calculations for a single celled bacterium.
b) Calculations of Hubert Yockey for random generation of a single molecule of iso-1-cytochrome c protein.
c) Calculations of Bradley and Thaxton for random production of a single protein.
d) Calculations of Harold Morowitz for single celled bacterium developing from accidental or chance processes.
Given the incredible improbability of life arriving from non-life.....do you really believe that life as we observe it today came to be by chance and natural process, and you are willing to base your life on that belief?
Send me a Freepmail so this point doesn't get lost, please.
It will be put on my "in" reading box and occasionally sighed over during the next six months :-)
Cheers!