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Possibility theory

Possibility theory is a mathematical theory for dealing with certain types of uncertainty and is an alternative to probability theory. It uses measures of possibility and necessity between 0 and 1, ranging from impossible to possible and unnecessary to necessary, respectively. Professor Lotfi Zadeh first introduced possibility theory in 1978 as an extension of his theory of fuzzy sets and fuzzy logic. Didier Dubois and Henri Prade further contributed to its development. Earlier, in the 1950s, economist G. L. S. Shackle proposed the min/max algebra to describe degrees of potential surprise.

Fuzzy logic: When a bottle is half full, it can be said that the level of truth of the proposition "The bottle is full" is 0.5. The word "full" is seen as a fuzzy predicate describing the amount of liquid in the bottle.

Possibility theory: There is one bottle, either completely full or totally empty. The proposition "the possibility level that the bottle is full is 0.5" describes a degree of belief. One way to interpret 0.5 in that proposition is to define its meaning as: I am ready to bet that it's empty as long as the odds are even (1:1) or better, and I would not bet at any rate that it's full.

There are four cases that can be interpreted as follows:


means that is necessary. is certainly true. It implies that .


means that is impossible. is certainly false. It implies that .


means that is possible. I would not be surprised at all if occurs. It leaves unconstrained.


means that is unnecessary. I would not be surprised at all if does not occur. It leaves unconstrained.


The intersection of the last two cases is and meaning that I believe nothing at all about . Because it allows for indeterminacy like this, possibility theory relates to the graduation of a many-valued logic, such as intuitionistic logic, rather than the classical two-valued logic.


Note that unlike possibility, fuzzy logic is compositional with respect to both the union and the intersection operator. The relationship with fuzzy theory can be explained with the following classic example.

Necessity logic[edit]

We call generalized possibility every function satisfying Axiom 1 and Axiom 3. We call generalized necessity the dual of a generalized possibility. The generalized necessities are related to a very simple and interesting fuzzy logic called necessity logic. In the deduction apparatus of necessity logic the logical axioms are the usual classical tautologies. Also, there is only a fuzzy inference rule extending the usual modus ponens. Such a rule says that if α and αβ are proved at degree λ and μ, respectively, then we can assert β at degree min{λ,μ}. It is easy to see that the theories of such a logic are the generalized necessities and that the completely consistent theories coincide with the necessities (see for example Gerla 2001).

Fuzzy measure theory

Logical possibility

Modal logic

Probabilistic logic

Random-fuzzy variable

Transferable belief model

Upper and lower probabilities

Dubois, Didier and Prade, Henri, "", Annals of Mathematics and Artificial Intelligence 32:35–66, 2002.

Possibility Theory, Probability Theory and Multiple-valued Logics: A Clarification

Gerla Giangiacomo, , Kluwer Academic Publishers, Dordrecht 2001.

Fuzzy logic: Mathematical Tools for Approximate Reasoning

Ladislav J. Kohout, "", Fuzzy Sets and Systems 25:357-367, 1988.

Theories of Possibility: Meta-Axiomatics and Semantics

"Fuzzy Sets as the Basis for a Theory of Possibility", Fuzzy Sets and Systems 1:3–28, 1978. (Reprinted in Fuzzy Sets and Systems 100 (Supplement): 9–34, 1999.)

Zadeh, Lotfi

and Ladislav J. Kohout, "Possible Automata", in Proceedings of the International Symposium on Multiple-Valued Logic, pp. 183-192, Bloomington, Indiana, May 13-16, 1975.

Brian R. Gaines