A Generalized Framework for Reasoning with Multi-Point Events

Allen's Interval Algebra (IA) and Vilain and Kautz's Point Algebra (PA) consider an interval and a point as basic temporal entities (i.e., events) respectively. However, in many real world situations we often need to deal with recurring events that include multiple points, multiple intervals or combinations of points and intervals. Recently, we presented a multiple-point event (MPE) framework to represent relations over recurring point events and showed that it can handle pointisable interval relations (SIA). We also showed that computing a minimal MPE network is a polynomial solvable problem. However, the MPE framework cannot correctly capture the relation between three points called a discontinuous point relation and this has not been satisfactorily addressed in the literature. In this paper, we extend MPE to a general framework that is expressive enough to represent discontinuous point relations and other complex situations which are relationships between single events (i.e., point-interval, and interval-interval relations), and clusters of events (i.e., recurring point-point and interval-interval relations). Further we developed a path-consistency algorithm for computing the minimal network for a generalised MPE network and improved our earlier path-consistency algorithm for MPE networks. We then present an analysis of experimental results on the implementation of these algorithms.

[1]  Henry A. Kautz,et al.  Constraint Propagation Algorithms for Temporal Reasoning , 1986, AAAI.

[2]  Lina Khatib,et al.  Reasoning with Multi-Point Events , 1996, Canadian Conference on AI.

[3]  Lina Khatib,et al.  Path Consistency in a Network of Non-Convex Intervals , 1993, IJCAI.

[4]  Bernhard Nebel Solving hard qualitative temporal reasoning problems: Evaluating the efficiency of using the ORD-Horn class , 1997 .

[5]  Sourmitra Dutta,et al.  Temporal reasoning in medical expert systems , 1988, Proceedings of the Symposium on the Engineering of Computer-Based Medical.

[6]  Peter van Beek,et al.  The design and experimental analysis of algorithms for temporal reasoning , 1996 .

[7]  Alexander Reinefeld,et al.  Effective Solution of Qualitative Interval Constraint Problems , 1992, Artif. Intell..

[8]  Alan K. Mackworth Constraint Satisfaction , 1985 .

[9]  P. V. Beek Exact and approximate reasoning about qualitative temporal relations , 1992 .

[10]  Massimo Poesio,et al.  Metric Constraints for Maintaining Appointments: Dates and Repeated Activities , 1991, AAAI.

[11]  Lawrence M. Fagan,et al.  Representation and Use of Temporal Information in ONCOCIN , 1985 .

[12]  Alan K. Mackworth Consistency in Networks of Relations , 1977, Artif. Intell..

[13]  Peter B. Ladkin,et al.  Time Representation: A Taxonomy of Internal Relations , 1986, AAAI.

[14]  M. Bismarck Medical expert systems using personal computers: Chytil, M.K. Engelbrecht, R. (eds.) (1987): Wilmslow: Sigma Press. 206 pp, ISBN 1-85058-047-2. , 1991 .

[15]  Peter van Beek,et al.  Exact and approximate reasoning about temporal relations 1 , 1990, Comput. Intell..

[16]  James F. Allen Maintaining knowledge about temporal intervals , 1983, CACM.

[17]  Lina Al-Khatib Reasoning with non-convex time intervals , 1995 .

[18]  Klaus Nökel Temporally Distributed Symptoms in Technical Diagnosis , 1991, Lecture Notes in Computer Science.

[19]  Peter van Beek,et al.  The Design and Experimental Analysis of Algorithms for Temporal Reasoning , 1995, J. Artif. Intell. Res..