These classic coding symbols have traditionally have been static values, at least, much of the code created during the past decade including my own is this way. However, much of the code created during this decade has been parallel in nature also. Programs constructed using parallel programming techniques and communicating objects allow easier handling of time-dependent sequences of states. Basic Patterns Neural networks perform pattern recognition by first training itself on a pattern. It builds a weight matrix on the input data representing the pattern.
Programs using genetic algorithms build state machines which are optimized to solve simple problems.
From this lower substrata the programmer is free to add an unlimited set of underlying methodologies in terms of structures and code to the neural state machines and evolutionary programming toolkits. Implementing cellular automata as a substrata on which to build thinking machines raises fundamental questions about the properties which the automata should exhibit. One such property is self-organization. Some people call this point a criticality which is a term used when speaking of physical systems approaching transition points. There is, at least, one feature which stands out clearly.