A General Qualitative Spatio-Temporal Model Based on Intervals

Many real-world problems involve qualitative reasoning about space and/or time. Actually, it is an adequate tool for dealing with situations in which information is not sufficiently precise. However, despite its numerous applications, it is difficult for people from outside the field to incorporate the required reasoning techniques into their methods. In this paper, we present a general, easy-to-use framework that integrates and solves the reasoning process of all qualitative models based on intervals. This framework has been divided into: (1) a representation magnitude and (2) the resolution of the reasoning process. Mainly, the developed method for solving the reasoning process is based on the definition of two algorithms: the qualitative sum and the qualitative difference. In addition, here, different instances of the model as well as some practical applications of them are presented

A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

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. This manuscript is under consideration for acceptance in TPLP.Comment: Paper presented at the 34th International Conference on Logic Programming (ICLP 2018), Oxford, UK, July 14 to July 17, 2018, 20 pages, LaTeX, 16 figure

A General Qualitative Spatio-Temporal Model Based on Intervals

Abstract Naming qualitative models allow humans to express spatio-temporal concepts such as "The cinemas are far away from my house". In colloquial terms, naming concepts are called relative. In this paper we introduce a general way to define naming qualitative models consisting of: (1) a representation magnitude, (2) the basic step of inference process and (3) the complete inference process. We present a general procedure to solve the representation magnitude and the basic step of inference process of qualitative models based on intervals. The general method is based on the definition of two algorithms: the qualitative sum and the qualitative difference

A General Qualitative Spatio-Temporal Model Based on Intervals

Abstract: Many real-world problems involve qualitative reasoning about space and/or time. Actually, it is an adequate tool for dealing with situations in which information is not sufficiently precise. However, despite its numerous applications, it is difficult for people from outside the field to incorporate the required reasoning techniques into their methods. In this paper, we present a general, easy-to-use framework that integrates and solves the reasoning process of all qualitative models based on intervals. This framework has been divided into: (1) a representation magnitude and (2) the resolution of the reasoning process. Mainly, the developed method for solving the reasoning process is based on the definition of two algorithms: the qualitative sum and the qualitative difference. In addition, here, different instances of the model as well as some practical applications of them are presented