# Exploring Unknown Universes in Probabilistic Relational Models

arXiv: https://arxiv.org/abs/2001.02021 · HTML: https://mlsanity.com/paper/2001.02021/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Jan 2020.

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

- [Lifting DecPOMDPs for Nanoscale Systems -- A Work in Progress](https://mlsanity.com/paper/2110.09152/) (2021)

## Abstract (arXiv)

Large probabilistic models are often shaped by a pool of known individuals (a universe) and relations between them. Lifted inference algorithms handle sets of known individuals for tractable inference. Universes may not always be known, though, or may only described by assumptions such as "small universes are more likely". Without a universe, inference is no longer possible for lifted algorithms, losing their advantage of tractable inference. The aim of this paper is to define a semantics for models with unknown universes decoupled from a specific constraint language to enable lifted and thereby, tractable inference.