---
title: "Maximum Entropy in Nilsson's Probabilistic Logic"
authors:
  - "Thomas B. Kane"
doi: ""
url: "https://ijcai.org/proceedings/1989/73"
pdf: "https://ijcai.org/proceedings/1989/0073.pdf"
venue: "Proceedings of the Eleventh International Joint Conference on Artificial Intelligence"
year: 1989
pages: "452-456"
track: "Automated Deduction"
keywords:
---

# Maximum Entropy in Nilsson's Probabilistic Logic

Thomas B. Kane

*Proceedings of the Eleventh International Joint Conference on Artificial Intelligence*, pages 452-456.

## 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.