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A form of many-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than precise. Example: The statement 'The room is warm' can be true to varying degrees depending on the context and interpretation.

Interprets probability as a measure of believability or confidence that an individual might possess about the occurrence of an event. Example: The probability of a hypothesis given some observed evidence can be updated with Bayes' theorem: $P(H|E) = \frac{P(E|H)P(H)}{P(E)}$.

Logical reasoning where the introduction of new information can invalidate previous conclusions. Example: If we learn that a bird can fly, but then learn it is a penguin, we revise our conclusion that it can't fly.

A type of formal logic that extends classical propositional and predicate logic to include modalities such as necessity and possibility. Example: 'It is necessary that 2+2=4' but 'It is possible that it will rain tomorrow'.

Logical fallacies that occur in reasoning about probability and uncertainty. Example: The gambler's fallacy is the incorrect belief that past events can influence the probability of future independent events.