You seem to have several basic misconceptions about how evolution through natural selection works. Basically what this boils down to is an argument from ignorance.
One thing that I think you'd be interested in knowing is that evolutionary principles have been used in computer programming and produce some amazing results:
After the unexpected success of Tierra, computer scientists began to explore whether similar techniques could be used to evolve real, useful code. Today, the state of the art is Genetic Programming or Evolutionary Programming, invented (and patented) in 1992 by John R. Koza of Stanford University.
Like Tierra, the "DNA" of Genetic Programming is a set of equations and operations, not just parameters; but instead of reaping the code that crashes and rewarding the code that copies itself in the smallest space, Evolutionary Programming measures how well each program does at solving a particular problem. The programs that do the worst are eliminated, and new strains of program code are bred by recombination, either with or without mutation.
The solutions produced by evolutionary programming resemble the solutions we find in the real world in several ways. To start with, they are very hard (or even impossible) to understand: the code makes no sense whatsoever to a human mind. It may use functions that seemingly have no logical relevance to the problem, like using trigonometry to solve a binary arithmetic problem. Typically evolved programs will consist of one long line of code, with literally hundreds of nested expressions.
Another characteristic of evolved solutions is that they're messy. They may include obviously unnecessary operations in one part of the code, yet be much more compact than any human programmer can achieve elsewhere. Think of the human eye: it has a far greater sensitivity than the best camera man can build, yet the retina is wired in backwards. The nerve cell wiring is on the inside of the eye, in the way of the light path; the brain processes the gaps out of the sensory data later on. If cameras were built like that, there would be wires going across the film, and you'd paint out the gaps on the prints when you got them back. Intelligent design? Hardly. The very idea is crazy. Yet to the blind process of evolution, it's perfectly adequate.
A third thing evolutionary solutions have in common is that they're unpredictable. Because we don't really understand how the evolved code works, we also don't know what conditions might make it stop working. A piece of evolved code that computed the best way to drive between two cities in the USA might behave bizarrely if asked about a city a mile across the border in Canada. Yet at the same time, evolved code is often much more robust than programmed code, so long as it has been tested against a wide enough range of sample problems. Because the code is evolved rather than designed, it doesn't have built into it all the assumptions a human programmer would make--and the Y2K problem is a good example of the value of not making obvious assumptions.
Robustness is good, but the single biggest advantage of Evolutionary Programming is the final thing it has in common with biological evolution: it can solve problems that humans are unable to solve, or come up with solutions better than any human solution. In the biological world, animals can climb stairs, avoid obstacles, catch prey, and do many other things that humans have failed to get a robot to do well. In the a-life world, there are evolved programs like the 22s in Tierra. Lockheed Martin have evolved code that works out how to maneuver spacecraft from one orientation to another. It achieves the goal within 2% of the theoretical minimum time -- which is around 10% faster than any human-written code can manage. Imitating nature even more closely may lead to further advances in genetic programming.
