How can a perfectly repeatable rule become hard to predict?
A rule can give exactly one next answer and still make long-range prediction difficult. The logistic recurrence, x-next = r × x × (1 − x), repeatedly feeds its output back into itself. For suitable settings, nearby starting values can separate greatly after repeated steps. Other settings settle down, so the parameter is part of the story.
Questions you could explore
- How does uncertainty in a starting value differ from randomness in the rule?
- What would comparing nearby numerical trajectories illustrate, and what would it leave unproved?
Start reading
- Robert M. May / Nature, 1976; Caltech archiveSimple mathematical models with very complicated dynamics
May introduces the logistic recurrence and shows why a simple deterministic rule can behave differently as its parameter changes. The conclusion suggests exploring the equation numerically.
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