Self-Improving Systems

Roland Olsson writes "A relatively easy way to construct "intelligent" systems that improve themselves practically ad infinitum is described at http://www-ia.hiof.no/~rolando/SIG/ Maybe Steven Spielberg's AI film is closer to reality than the general public knows *smile*?"

Comments

My own experiments with evolved code

[melquiades]

In college, I did a project in which I attempted to evolve programs for Core Wars, in which two programs running in a virtual machine language basically attempt to overwrite each other's memory space.

My algorithm started with random programs and pitted them against each other in the Core Wars arena. The fitness function was simple: programs that beat other programs got higher ratings. Top-rated programs would "breed", and all programs would mutate. The hope was that after time, successful warriors would evolve.

And, lo and behold, they did! My algorithm "evolved" some simple bombers -- not nearly as good as what a human would write, but amazing considering I put no knowledge about strategy into the algorithm, and started with random core wars code.

Ah, but (there's always a but) I found that there was no significant correlation between how successful a warrior was and how many generations of crossover went into it. In other words, the genetic algorithm did no better than an algorithm which simply selected lots of random programs and kept the ones that work. So actually, my result was not very impressive at all -- I was basically doing a brute force random search for programs, and happened to find a few.

Others might get much better results with different languages, because Core Wars machine code does not lend itself to crossover (i.e. it's had to merge two Core Wars programs into a better program). Functional languages do a bit better with this. But I really doubt that Genetic Algorithms will prove useful in the near future for generating any sort of code that wouldn't be trivially easy for a human to write.