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Decision tree vs. Turing machine

Variation in overall size, branch angle/length/node distance influence the resulting number of possible steps, as well a the limited run time and state complexity does. This also lets "fail often, fail early" look like that simple approach for a massive wide step zig zag approach to life; only if assuming no life-relevant costs per step, that is.

Still, a state machine with loops allows for second chances in general, while the underlying environment also changes in parallel. So your outlook for the second try might as well be better.

To describe a backwards directed re-play, a decision tree might be a tempting structure. But just because the "truth" is too complex to describe and not visible to you in its entirety anyway.

Don't get discouraged by these kind of undercomplex views on life. There's still lot of environmental problems/limitations to be solved, to make everybody's run a bit smoother and less dependend on their environment, though, even though, or because, all the runs and the environment are basically the same thing.



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