I am an undergraduate currently studying computer science at Rutgers University. My current interests include machine learning, programming languages, and user interfaces. I would like to one day be able to use learning algorithms to allow programs to dynamically mutate their interfaces with user demand. When I am not coding, I am usually running my local Linux User Group, and lockpicking.
Using Block Automata to Simulate Modular Robotics
For this project, I have used a block automaton to model modular robots. The evolution of this automaton allowed me to easily model the motion of the modular robots. Each step of the motion can be modeled by a series of rules that define how it moves. This gives me the ability to have entire deterministic behaviors that react dynamically to their environment. The behaviors can then be enumerated as rules in the system, which allows exploration of a behavior space. The aim has been to find interesting behaviors and to determine how much of that behavior was situational. This was done by placing multiple robots with the same rule behavior into different places in the environment and observing how they behave.
Rule chosen: 3044695274
I found 3044695274 in the space of left-neighbor, four-color, 1/2-range rules. It has a very complicated pattern to it but it manages to just barely stay at the edge of coherence. You can see patterns in it. If you stare long enough there is even a feel that you just might comprehend it all.