Sum of the parts?
Just a quick note to myself here on a realization.
Game Theory and FSM
Finite States Machines (FSM), e.g. Moore Machines
Moore’s Machines and Ashby’s transition matrices
Moore’s machines and binary representations
Binary representations and RLCS
RLCS and RL
Transition Matrices and Graphs
Graphs & infectious processes representation (?)
Schelling’s model & Agents evolving and making decisions in a simulated world
So RL, but not only!
Now:
Can I use RLCS to create optimize Agents that in turn are representations of FSMs, thereby representing rather complex decision processes, all using a simple binary representation (maybe?), and hence allowing for rather complex modelling with all the pieces of the puzzle almost already implemented?
I need to learn how to represent FSMs as binary strings to represent them as agents compatible with the RLCS code.
But then… What could be done?