I've read it many times. It introduced me to the idea of using self-modifying programs. I've built several prototypes that use their exact instruction set, but I haven't found a way to guide the evolution in a desired direction yet. The self-modifying aspect can be quite destructive to the genome.
I have to dig up my old code. I remember It was difficult to observe and identify the replicators. I don't remember following their "tracker" idea.
As you've mentioned, it can be quite self destructive, so I've been experimenting with the instruction set itself.
Each cell is one of 256 values, where only 10 of those values are instructions. In addition, the original instruction set is not uniformly distributed. This means that the likelihood of mutating destructively is highly affected by ratio of valid instructions and their distribution. For example, a cell with value 0xD0 is much less likely to mutate to a valid instruction than a cell of value 0x0D (assuming UTF-8). By playing with these parameters to make the state space smaller, I've seen significantly different levels of stability.
I'd love to follow your work if you share it anywhere!
I've read it many times. It introduced me to the idea of using self-modifying programs. I've built several prototypes that use their exact instruction set, but I haven't found a way to guide the evolution in a desired direction yet. The self-modifying aspect can be quite destructive to the genome.