Their first task was easy. Can the digital organisms I wrote, called “figures,” learn to call a good command and avoid a bad one?

My first job was easy. It only took 6 lines of code. Each digital creature, each “figure,” has a certain amount of energy.

Figure.energy = 12,168;

Each time a figure has a turn, (when they execute one command,) the energy level drops.

Energy=energy-1;

When a figure is out of energy, it dies. It is completely deleted from the system, leaving behind it’s children, if it had any.

If (figure.energy < = 0) Death.kill(figure) [scary music!] End if Continue reading Their first task was easy →

It’s about time I tried using my artificial life as an artificial intelligence. It’s been the goal since day one. Before I could do that, I had to come up with the algorithm in the first place, and then make sure that the figures could actually evolve. To evolve, they need to change, and some of those changes should help them survive and reproduce, passing on their successful tricks to their offspring.
Continue reading It’s about time I tried using my artificial life as an artificial intelligence →

I’m sitting on the edge of a binary ocean, casting hyperdimensional nets into the infinite waters of possible programs. My digital creatures, which I call “figures,” will run on my computer for hours, until I finally catch something.
Continue reading It’s like fishing. →

Written on Wednesday October3, 2018

Small sample sizes and all those caveats.

I’m tossing out the number of figures being born as a threshold. That will pop out of any of them at any time, and it’s just luck. One of them starts reproducing very quickly, and happens to find a window of relatively few mutation’s, and then skate on through to the finish line.

I retested the first five populations, snagged with a threshold of 100 and 100,000, if memory servs me. Looking at the most mutations given to a population, side by side results, first five and latest five.
Continue reading It bloody well works! →