---
title: "From knowledge-based programs to graded belief-based programs, part II: off-line reasoning"
authors:
  - "Noël Laverny"
  - "Jérôme Lang"
doi: ""
url: "https://ijcai.org/proceedings/2005/121"
pdf: "https://ijcai.org/proceedings/2005/0121.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "497-501"
track: ""
keywords:
---

# From knowledge-based programs to graded belief-based programs, part II: off-line reasoning

Noël Laverny, Jérôme Lang

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 497-501.

## Abstract

Belief-based programs generalize knowledgebased programs [Fagin et al., 1995] by allowing for incorrect beliefs, unreliable observations, and branching conditions that refer to implicit graded beliefs, such as in “while my belief about the direction to the railway station is not strong enough do ask someone”. We show how to reason off-line about the possible executions of a belief-based program, which calls for introducing second-order uncertainty in the model.