The first pass of a simulation routine, written in LabVIEW, is working. I probably spent more time debugging the handshaking routine than anything else, but it’s working now. I can generate a seed code-worm that starts at cell (0, 0) then travels across to a destination cell.
In this debug stage, I need to display all the registers so I can watch what is happening within each of the individual cells. This verbose display mode means that I can only fit a 4x4 display array on my monitor. But a 4x4 array, at this first pass stage, was good enough to get things working.
I have an old Windows-XP legacy system that I kept available for periodic maintenance work on projects that I did for clients years earlier. Now that I’m retied and don’t need it anymore; time to turn it into Linux system. I’ve ordered a new hard drive and will upgrade this old XP system to Linux running Debian. The hard drive should arrive next week. At which point I’ll start the second phase of the array processor simulation project.
On the cellular automata front, it only took a little bit of research to find out that Stephen Wolfram, of Mathematica fame, has already done a significant amount of work in this area. I checked his book out from the library, “A New Kind of Science” and have started reading it.
My intent is to start with duplicating some of the classic cellular automata featured on YouTube, like the Game of Life and Langton’s Ant. The challenge is going to be how to visualize the time evolution of such systems; especially in the case of arrays on the order of 100x100 and bigger. Needing to display the progress of such a large array on a standard monitor means I can’t use much more than a 10x10 pixel area per display cell. Outputting numbers in this case is out of the question. So, what I have to explore next is ways to use colors to encode what each cell is doing.
For the simple examples I will be starting with, just displaying either a light or dark shaded area will be sufficient. But as I progress to more complicated relationships between the cells I’ll need to try something different. One obvious trick is to use the assembly language “org” instruction to partition various sections of each cell’s program-code into different segments of program-memory. Then assign different colors to each of these code segments; that way encoding the program-counter as a color will indicate which subroutine is active at any one time. What other cell-variables will be relevant to visualize, and how to visualize them with color-encoding is something I need to work on in the weeks ahead.
Next, is to start making “evolution” videos of these two-dimensional cellular automata and watch to see if any patterns appear to emerge. And regarding this effort, something worth noting is that when it comes to pattern recognition, the human brain is the best visual processing system we have access to. Even Google, Facebook, Stanford, MIT and the rest, even with their unique access to massive amounts of computational horsepower, and even using advanced techniques like deep learning, are still struggling to visually recognize a cat in a picture; something that humans can do quite easily.
I need to remember that my goal is not to just recreate work others have already done, but to explore the possibilities of using code-worms as a way of stabilizing the evolution of cellular automata so that they will stay stationary and not move off screen. If I can get that far, then the next question to explore will be whether these stationary automata can be used as computational engines to process an input to an output stream? Specifically, I’m curious if an automata could be used to function as a Szilard’s Engine or a Maxwell’s demon.
On a second note: It has been over 20 years since I left physics and went into engineering. I’m afraid my math skills have gotten quite rusty. So, in an effort to get my skills backup to par, I’ll be working through my old textbook on math logic “Logic for Mathematicians” by A. G. Hamilton. and starting to work through the YouTube video series on the “Theory of Computation.”