evaluations

Over the weekend I finished up the Genetic Algorithm implementation, and fine tuned it. On the first runs I was getting really low output, so I tweaked the population generator. At the time I thought it was cheating, but my reasoning was: if I need to build a bridge and I start out with random materials, I know that clouds will not be good, and I know that keeping bricks together with gum will be no good either. Turns out this is called seeding the population, and its a task for this week. ( ^ . ^)  I change the method to now spit out random numbers between plus and minus 20 for now.
I made a new class that would automatically run a simulation of N parameters, X amount of time and would present the outcome in Excel friendly format, so all I have to do is copy the file content into a excel doc and output a graph. I ran the program for 20 simulations with 15 generations and I got some cool results. After the about three generations every generation after that just hovers around some number. I think its interesting that all the simulations showed this effect. I only did 20 simulations of 15 generations of 15 individuals  because I wanted to get all the bugs out of the code and my computer is.. lets just say it is not top of the line, its good, just not intel good.