A Divide-and-Conquer Approach for Solving Interval Algebra Networks

Abstract

Deciding consistency of constraint networks is a fundamental problem in qualitative spatial and temporal reasoning. In this paper we introduce a divide-and-conquer method that recursively partitions a given problem into smaller sub-problems in deciding consistency. We identify a key theoretical property of a qualitative calculus that ensures the soundness and completeness of this method, and show that it is satisfied by the Interval Algebra (IA) and the Point Algebra (PA). We develop a new encoding scheme for IA networks based on a combination of our divide-and-conquer method with an existing encoding of IA networks into SAT. We empirically show that our new encoding scheme scales to much larger problems and exhibits a consistent and significant improvement in efficiency over state-of-the-art solvers on the most difficult instances. Jason Jingshi Li, Jinbo Huang, Jochen Renz

Cite

Text

Li et al. "A Divide-and-Conquer Approach for Solving Interval Algebra Networks." International Joint Conference on Artificial Intelligence, 2009.

Markdown

[Li et al. "A Divide-and-Conquer Approach for Solving Interval Algebra Networks." International Joint Conference on Artificial Intelligence, 2009.](https://mlanthology.org/ijcai/2009/li2009ijcai-divide/)

BibTeX

@inproceedings{li2009ijcai-divide,
  title     = {{A Divide-and-Conquer Approach for Solving Interval Algebra Networks}},
  author    = {Li, Jason Jingshi and Huang, Jinbo and Renz, Jochen},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2009},
  pages     = {572-577},
  url       = {https://mlanthology.org/ijcai/2009/li2009ijcai-divide/}
}