more input. And often the actual form of this train of thought is influenced by memory we have developed from inputs in the past—making it not necessarily repeatable even with exactly the same input.

But it seems likely that the individual steps in each train of thought follow quite definite underlying rules. And the crucial point is then that I suspect that the computation performed by applying these rules is often sophisticated enough to be computationally irreducible—with the result that it must intrinsically produce behavior that seems to us free of obvious laws.

Undecidability and Intractability

Computational irreducibility is a very general phenomenon with many consequences. And among these consequences are various phenomena that have been widely studied in the abstract theory of computation.

In the past it has normally been assumed that these phenomena occur only in quite special systems, and not, for example, in typical systems with simple rules or of the kind that might be seen in nature. But what my discoveries about computational irreducibility now suggest is that such phenomena should in fact be very widespread, and should for example occur in many systems in nature and elsewhere.

In this chapter so far I have mostly been concerned with ongoing processes of computation, analogous to ongoing behavior of systems in nature and elsewhere. But as a theoretical matter one can ask what the final outcome of a computation will be, after perhaps an infinite number of steps. And if one does this then one encounters the phenomenon of undecidability that was identified in the 1930s.

The pictures on the next page show an example. In each case knowing the final outcome is equivalent to deciding what will eventually happen to the pattern generated by the cellular automaton evolution. Will it die out? Will it stabilize and become repetitive? Or will it somehow continue to grow forever?

One can try to find out by running the system for a certain number of steps and seeing what happens. And indeed in example (a) this approach works well: in only 36 steps one finds that the pattern

From Stephen Wolfram: A New Kind of Science [citation]