
We discuss the rule of inference called the entailment principle which plays a significant role in the possibilistic reasoning used in the theory of approximate reasoning. We extend this principle to situations in which the knowledge is a type of combination of possibilistic and probabilistic information which we call Dempster-Shafer granules. We discuss the conjunction of these D-S granules and show that Dempster's rule of combination is a special application of conjunction followed by a particular implementation of the entailment principle.
Artificial intelligence, entailment, Fuzzy sets and logic (in connection with information, communication, or circuits theory), combination of possibilistic and probabilistic information, approximate reasoning, Fuzzy logic; logic of vagueness, possibilistic reasoning
Artificial intelligence, entailment, Fuzzy sets and logic (in connection with information, communication, or circuits theory), combination of possibilistic and probabilistic information, approximate reasoning, Fuzzy logic; logic of vagueness, possibilistic reasoning
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