Conditional logic and the Principle of Entropy

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摘要

The conditional three-valued logic of Calabrese is applied to the language of conditionals on propositional variables with finite domain. The conditionals in serve as a means for the construction and manipulation of probability distributions respecting the Principle of Maximum Entropy and of Minimum Relative Entropy. This principle allows a sound inference even in the presence of uncertain evidence. The inference is directed, it respects a probabilistic version of Modus Ponens—not of Modus Tollens—, it permits transitive chaining and supports a cautious monotony. Conjunctive, conditional and material deduction are manageable in this probabilistic logic, too. The concept is not merely theoretical, but enables large-scale applications in the expert system-shell SPIRIT.

论文关键词:Conditional logic,Expert system,Inference,Maximum entropy,Probabilistic logic,SPIRIT

论文评审过程:Received 12 May 1999, Revised 21 August 1999, Available online 7 February 2000.

论文官网地址:https://doi.org/10.1016/S0004-3702(99)00105-8