Efficient Methods for Qualitative Spatial Reasoning

TL;DR

This paper empirically investigates efficient algorithms for qualitative spatial reasoning in the RCC8 framework, demonstrating that adapted temporal reasoning algorithms and heuristic combinations can solve large, complex instances effectively.

Contribution

It introduces the adaptation of temporal reasoning algorithms to RCC8 and identifies maximal tractable subsets, improving solution efficiency for large spatial reasoning problems.

Findings

Heuristic methods successfully solve most hard instances in the phase transition region.

Adapting temporal reasoning algorithms to RCC8 is effective for large problem instances.

Maximal tractable subsets are key to efficient qualitative spatial reasoning.

Abstract

The theoretical properties of qualitative spatial reasoning in the RCC8 framework have been analyzed extensively. However, no empirical investigation has been made yet. Our experiments show that the adaption of the algorithms used for qualitative temporal reasoning can solve large RCC8 instances, even if they are in the phase transition region -- provided that one uses the maximal tractable subsets of RCC8 that have been identified by us. In particular, we demonstrate that the orthogonal combination of heuristic methods is successful in solving almost all apparently hard instances in the phase transition region up to a certain size in reasonable time.