---
title: "Property Persistence in the Situation Calculus"
authors:
  - "Ryan F. Kelly"
  - "Adrian R. Pearce"
doi: ""
url: "https://ijcai.org/proceedings/2007/314"
pdf: "https://ijcai.org/proceedings/2007/0314.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "1948-1952"
track: ""
keywords:
---

# Property Persistence in the Situation Calculus

Ryan F. Kelly, Adrian R. Pearce

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 1948-1952.

## Abstract

We develop an algorithm for reducing universally quantified situation calculus queries to a form more amenable to automated reasoning. Universal quantification in the situation calculus requires a second-order induction axiom, making automated reasoning difficult for such queries. We show how to reduce queries about property persistence, a common family of universally-quantified query, to an equivalent form that does not quantify over situations. The algorithm for doing so utilizes only first-order reasoning. We give several examples of important reasoning tasks that are facilitated by our approach, including checking for goal impossibility and reasoning about knowledge with partial observability of actions.