decision theory Decision theory (or the theory of choice; not to be confused with choice theory) is a branch of applied probability theory concerned with the theory of making decisions based on assigning probabilities to various factors and assigning numerical ...

, a pignistic probability is a

probability Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speakin ...

that a rational person will assign to an option when required to make a decision. A person may have, at one level certain beliefs or a lack of knowledge, or uncertainty, about the options and their actual likelihoods. However, when it is necessary to make a decision (such as deciding whether to place a

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), the behaviour of the rational person would suggest that the person has assigned a set of regular probabilities to the options. These are the ''pignistic probabilities''. The term was coined by

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, and stems from the Latin ''pignus'', a bet. He contrasts the ''pignistic'' level, where one might take action, with the ''credal'' level, where one interprets the state of the world: :The

transferable belief model The transferable belief model (TBM) is an elaboration on the Dempster–Shafer theory (DST), which is a mathematical model used to evaluate the probability that a given proposition is true from other propositions which are assigned probabilities. ...

is based on the assumption that beliefs manifest themselves at two mental levels: the ‘credal’ level where beliefs are entertained and the ‘pignistic’ level where beliefs are used to make decisions (from ‘credo’ I believe and ‘pignus’ a bet, both in Latin). Usually these two levels are not distinguished and probability functions are used to quantify beliefs at both levels. The justification for the use of probability functions is usually linked to “rational” behavior to be held by an ideal agent involved in some decision contexts. A ''pignistic probability transform''Dezert, J., Smarandache, F., Daniel, M., "The Generalized Pignistic Transformation", Proc 7th Intl Conf. Information Fusion, Stockholm, Sweden (2004) pp. 384–391 will calculate these pignistic probabilities from a structure that describes belief structures.

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