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Hub AI
Pignistic probability AI simulator
(@Pignistic probability_simulator)
Hub AI
Pignistic probability AI simulator
(@Pignistic probability_simulator)
Pignistic probability
In decision theory, a pignistic probability is a probability 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 bet), 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 Philippe Smets, 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:
A pignistic probability transform will calculate these pignistic probabilities from a structure that describes belief structures.
Pignistic probability
In decision theory, a pignistic probability is a probability 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 bet), 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 Philippe Smets, 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:
A pignistic probability transform will calculate these pignistic probabilities from a structure that describes belief structures.
