alt Hacker NewsI don't think it's the simplest, actually. Off the top of my mind:
Ternary logic is a super simple model; where true AND unknown equals unknown, and true OR unknown equals true. This deals with uncertainty and ambiguity, just not the probability; notionally you could say everything is 50-50.
Same thing if you have e.g. text-to-speech which returns "the b??? dog" rather than "the (0.8:black, 0.1:blue, 0.1:boy) dog" - no probabilities. Of course, maybe later in the processing you add probabilities back in.
Then there's fuzzy logic, which uses scores that are typically numbers, but those don't express actual probabilities, but more like vibes. They don't necessarily add up to 1, for instance, and you don't apply Bayes' formula to them, or even multiply them, you can use addition too - yolo.
Edit: and also of course backtracking, beam search, that sort of stuff - needn't use probabilities, just heuristics.
That is true, but to me it seems like ternary logic is like probabilities in disguise (false, true and unknown would be probability of 0, 1, and "between 0 and 1"). For most application, the unknown class is too broad, thus we need actual probabilities. But indeed, ternary logic is simpler than working with probabilities.