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Enhancing the inference mechanism of Nilsson's probabilistic logic
Author(s) -
Kane Thomas B.
Publication year - 1990
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550050504
Subject(s) - probabilistic logic , probabilistic logic network , conditional probability , computer science , probabilistic argumentation , logical consequence , inference , theoretical computer science , probabilistic ctl , rule of inference , artificial intelligence , algorithm , mathematics , probabilistic analysis of algorithms , autoepistemic logic , description logic , multimodal logic , statistics
Nilsson's Probabilistic Logic is a set‐theoretic mechanism for reasoning with uncertainty. We propose a new way of looking at the probability constraints enforced by the framework, which allows the expert to include conditional probabilities in the semantic tree, thus making Probabilistic Logic more expressive. the meaning of entailment in an uncertain environment is explored. an algorithm is presented which will find the maximum entropy point probability for a rule of entailment without resorting to solution by iterative approximation. Also presented are a number of methods for employing the conditional probabilities.