---
title: "Answer Update for Rule-Based Stream Reasoning"
authors:
  - "Harald Beck"
  - "Minh Dao-Tran"
  - "Thomas Eiter"
doi: ""
url: "https://ijcai.org/proceedings/2015/388"
pdf: "https://ijcai.org/proceedings/2015/0388.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "2741-2746"
track: "Special Track on Knowledge Representation and Reasoning"
keywords:
---

# Answer Update for Rule-Based Stream Reasoning

Harald Beck, Minh Dao-Tran, Thomas Eiter

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 2741-2746.

## Abstract

Stream reasoning is the task of continuously deriving conclusions on streaming data. To get results instantly one evaluates a query repeatedly on recent data chunks selected by window operators. However, simply recomputing results from scratch is impractical for rule-based reasoning with semantics similar to Answer Set Programming, due to the trade-off between complexity and data throughput. To address this problem, we present a method to efficiently update models of a rule set. In particular, we show how an answer stream (model) of a LARS program can be incrementally adjusted to new or outdated input by extending truth maintenance techniques. We obtain in this way a means towards practical rule-based stream reasoning with nonmonotonic negation, various window operators and different forms of temporal reference.