English

Towards Explainable Inference about Object Motion using Qualitative Reasoning

Artificial Intelligence 2018-07-31 v1

Abstract

The capability of making explainable inferences regarding physical processes has long been desired. One fundamental physical process is object motion. Inferring what causes the motion of a group of objects can even be a challenging task for experts, e.g., in forensics science. Most of the work in the literature relies on physics simulation to draw such infer- ences. The simulation requires a precise model of the under- lying domain to work well and is essentially a black-box from which one can hardly obtain any useful explanation. By contrast, qualitative reasoning methods have the advan- tage in making transparent inferences with ambiguous infor- mation, which makes it suitable for this task. However, there has been no suitable qualitative theory proposed for object motion in three-dimensional space. In this paper, we take this challenge and develop a qualitative theory for the motion of rigid objects. Based on this theory, we develop a reasoning method to solve a very interesting problem: Assuming there are several objects that were initially at rest and now have started to move. We want to infer what action causes the movement of these objects.

Keywords

Cite

@article{arxiv.1807.10935,
  title  = {Towards Explainable Inference about Object Motion using Qualitative Reasoning},
  author = {Xiaoyu Ge and Jochen Renz and Hua Hua},
  journal= {arXiv preprint arXiv:1807.10935},
  year   = {2018}
}
R2 v1 2026-06-23T03:17:54.849Z