Authors: George Baryannis, Ilias Tachmazidis, Sotiris Batsakis, Grigoris Antoniou, Mario Alviano, Timos Sellis and Pei-Wei Tsai
Paper Information
Title: | A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming |
Authors: | George Baryannis, Ilias Tachmazidis, Sotiris Batsakis, Grigoris Antoniou, Mario Alviano, Timos Sellis and Pei-Wei Tsai |
Proceedings: | ICLP Proceedings of ICLP 2018 |
Editors: | Paul Tarau and Alessandro Dal Palu' |
Keywords: | Answer Set Programming, Spatial Reasoning, Qualitative Reasoning, Trajectory |
Abstract: | ABSTRACT. Spatial information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as bus routes planning. Representing and reasoning on trajectories is a specific case of qualitative spatial reasoning that focuses on moving objects and their paths. In this work, we propose two versions of a trajectory calculus based on the allowed properties over trajectories, where trajectories are defined as a sequence of non-overlapping regions of a partitioned map. More specifically, if a given trajectory is allowed to start and finish at the same region, 6 base relations are defined (TC-6). If a given trajectory should have different start and finish regions but cycles are allowed within, 10 base relations are defined (TC-10). Both versions of the calculus are implemented as ASP programs; we propose several different encodings, including a generalised program capable of encoding any qualitative calculus in ASP. All proposed encodings are experimentally evaluated using a real-world dataset. Experiment results show that the best performing implementation can scale up to an input of 250 trajectories for TC-6 and 150 trajectories for TC-10 for the problem of discovering a consistent configuration, a significant improvement compared to previous ASP implementations for similar qualitative spatial and temporal calculi. |
Pages: | 20 |
Talk: | Jul 15 15:00 (Session 105C: Learning and Reasoning) |
Paper: |