On Fuzzy Logic and Uncertainty in AI

UNCERTAINTY IN ARTIFICIAL INTELLIGENCE 

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FUZZY LOGIC

BAYESIAN NETWORKS

MARKOV CHAINS

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Uncertainty exists in human and business decision making, in particular, on important decisions. In essence, fuzziness and randomness are two distinct components (or aspects) of uncertainty. This can be paraphrased by stating that there are two kinds of uncertainty: One derived from fuzziness (Epistemic) and another derived from randomness (Aleatoric). These two components and aspects of uncertainty can lead to further understand the human reasoning under uncertain circumstances.  The models introduced here involve:

• ·      Probability Theory 
• ·      Fuzzy Logic Theory
• ·      Evidence Theory
• ·      Possibility Theory

 I briefly discussed LaPlace Inverse Probability Theorem, better known as Bayes Rule, as named by Poincaré.

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