Efficiently Enforcing Path Consistency on Qualitative Constraint Networks by Use of Abstraction

Author:

Sioutis Michael1,Condotta Jean-François1

Affiliation:

1. Université d'Artois, CRIL-CNRS UMR 8188, Lens, France

Abstract

Partial closure under weak composition, or partial weak path-consistency for short, is essential for tackling fundamental reasoning problems associated with qualitative constraint networks, such as the satisfiability checking problem, and therefore it is crucial to be able to enforce it as fast as possible. To this end, we propose a new algorithm, called PWCα, for efficiently enforcing partial weak path-consistency on qualitative constraint networks, that exploits the notion of abstraction for qualitative constraint networks, utilizes certain properties of partial weak path-consistency,and adapts the functionalities of some state-of-the-art algorithms to its design. It is worth noting that, as opposed to a related approach in the recent literature, algorithm PWCα is complete for arbitrary qualitative constraint networks. The evaluation that we conducted with qualitative constraint networks of the Region Connection Calculus against a competing state-of-the-art generic algorithm for enforcing partial weak path-consistency, demonstrates the usefulness and efficiency of algorithm PWCα.

Publisher

International Joint Conferences on Artificial Intelligence Organization

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Knowledge Discovery from Qualitative Spatial and Temporal Data;2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI);2022-10

2. Towards Robust Qualitative Spatio-Temporal Reasoning for Hybrid AI Systems;2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE);2021-11-26

3. Just-In-Time Constraint-Based Inference for Qualitative Spatial and Temporal Reasoning;KI - Künstliche Intelligenz;2020-04-13

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