As I prep for a summer in Vermont to study NKS and automata, I’m starting to build research and project concepts. My focus, as it stands now, is to some how take concepts from behaviorism (schedules of reinforcement, operants, rewards and punishers) and use automata to study them computationally. This is not trivial nor is their any indication yet that it will be valuable.
I’m attempting to mash the two lines of inquiry because there really isn’t an accurate nor reliable mathematical foundation in behaviorism even though the experimental and explanatory power of behaviorism is substantial and proven.
IF, and it’s a big IF, cellular automata and a computational (as opposed to a partial differential equation set) can model the concepts in behaviorism we will have a very exciting line of research to chase down. Modeling and researching complex human behaviors (those with lots of overlapping and interacting schedules and complex environments) has been impossible experimentally and mathematically – only the most basic of behavior is possible to study and it usually has to be isolated to the point where it looses the environment it so richly interacts with. If we can devise cellular automata capable of showing operant conditioning in ever more realistic environments, we could set up very complicated models without all the laboratory fixings….and so much more.
Note that I am not studying Social Behavior or Social Dynamics or Swarms – not in the typical “what you read on the blogs” sense. A lot of work has been done in that area even with automata. The study of individual behavior (how a particular individual responds and learns) needs more research. I believe that a more thorough understanding of individual behavior will lead to stronger more robust social behavior models – as social behavior is emergent from individual behavior.
Anywho… to whet yer whistle read some fun stuff from Alastar Hewitt on mathematical reinforcement learning and CA