Maximum Entropy in Nilsson's Probabilistic Logic

Kane, Thomas B

Abstract

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. An algorithm is presented which will find the maximum entropy point probability for a rule of entailment without resorting to solution by iterative approximation. The algorithm works for both the propositional and the predicate logic. Also presented are a number of methods for employing the conditional probabilities.

Citation

Kane, T. B. (1989, August). Maximum Entropy in Nilsson's Probabilistic Logic. Presented at International Joint Conference on Artificial Intelligence

• Presentation Conference Type: Conference Paper (published)
• Conference Name: International Joint Conference on Artificial Intelligence
• Start Date: Aug 15, 1989
• End Date: Aug 19, 1989
• Acceptance Date: Jan 10, 1989
• Publication Date: Aug 15, 2017
• Deposit Date: Feb 13, 2018
• Publisher: International Joint Conferences on Artificial Intelligence Organization
• Pages: 452-457
• Book Title: Proceedings of the 11th International Joint Conference on Artificial Intelligence.
• Chapter Number: NA
• ISBN: 1-555860-094-9
• Keywords: Reasoning, probability,
• Public URL: http://researchrepository.napier.ac.uk/Output/1007020