Numerical representations of acceptance
作者： Henri Prade , Didier Dubois
DOI:
关键词: Conjunction (grammar) 、 Negation 、 Monotonic function 、 Property (philosophy) 、 Mathematics 、 Artificial intelligence 、 Proposition 、 Mathematical economics 、 Set (psychology) 、 Belief revision 、 Logical consequence
摘要: Accepting a proposition means that our confidence in this is strictly greater than the its negation. This paper investigates subclass of uncertainty measures, expressing confidence, capture idea acceptance, what we call acceptance functions. Due to monotonicity property entails any logical consequences. In agreement with belief set (in sense Gardenfors) must be closed under consequence, it also required separate two propositions entail their conjunction. Necessity (and possibility) measures agree view while probability and functions generally do not. General properties are established. The motivation behind work investigation setting for revision more general one proposed by Alchourron, Gardenfors Makinson, connection notion conditioning.
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