# Probabilistic Disjunctive Logic Programming

arXiv: https://arxiv.org/abs/1302.3592 · HTML: https://mlsanity.com/paper/1302.3592/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Feb 2013.

## Built on by (most cited first, 1 of 1)

- [The generalised distribution semantics and projective families of distributions](https://mlsanity.com/paper/2211.06751/) (2022)

## Abstract (arXiv)

In this paper we propose a framework for combining Disjunctive Logic Programming and Poole's Probabilistic Horn Abduction. We use the concept of hypothesis to specify the probability structure. We consider the case in which probabilistic information is not available. Instead of using probability intervals, we allow for the specification of the probabilities of disjunctions. Because minimal models are used as characteristic models in disjunctive logic programming, we apply the principle of indifference on the set of minimal models to derive default probability values. We define the concepts of explanation and partial explanation of a formula, and use them to determine the default probability distribution(s) induced by a program. An algorithm for calculating the default probability of a goal is presented.