In the logics we are here described above, what we have been concerned with truth: whether propositions and sentences are true. Moreover, with some natural language statements, it's too tough to assign a "true" or "false" value. For example we notice that, is the sentence: "Prince Charles is tall" true or false? Some people might say true, and others may say it is false, so there's an underlying probability which we may also want to represent.
This can be achieved with so-known as "fuzzy" logics. The originator of fuzzy logics, Lotfi Zadeh, advocates not so much thinking about particular fuzzy logics as like, but rather thinking of the "fuzzification" of current theories and analysis, and this is beginning to play a part in "AI". The proper combination of logics with theories of probability, and programming agents to reason in the light of uncertain knowledge are important areas of ‘AI" research. Various kinds of representation schemes like as Stochastic Logic Programs have an aspect of both logic and probability.