EvIA - Evidential Interval Algebra and Heuristic Backtrack-Free Algorithm

  • Authors:

  • S. Durga Bhavani;Arun K. Pujari

  • Affiliations:

  • Department of Computer and Information Sciences, University of Hyderabad, Hyderabad - 500046 India akpcsrs@uohyd.ernet.in;Department of Computer and Information Sciences, University of Hyderabad, Hyderabad - 500046 India akpcs@uohyd.ernet.in

  • Venue:
  • Constraints
  • Year:
  • 2004

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Abstract

The Interval Algebra (IA) framework for temporal reasoning encodes indefinite knowledge in terms of disjunctions of relations. Many problems arising in practice can have evidences from past or from other external sources to indicate that some relations in a disjunction may be more probable than others. IA framework is inadequate to encode this information. The aim of the present study is two fold. First, to extend IA framework by associating numeric weights to the relations for capturing additional information and provide a reasoning methodology for the extended framework. Second, to apply the extended framework for developing a heuristic algorithm which finds a solution of the conventional IA network problem without backtrack. We make use of well-known evidential reasoning techniques to develop the new framework, Evidential Interval Algebra (EvIA). EvIA is an augmentation of interval algebra with evidential techniques. The constraint, constraint operators namely converse, composition and intersection, and path consistency algorithm of interval algebra are overlayed by evidential function and evidential operations to get enhanced expressiveness and efficient reasoning capability. The efficiency of the EvIA framework is demonstrated in the form of a heuristic which finds a solution of the interval algebra network without backtrack. Experimental results of the heuristic algorithm reveal that the algorithm is sound and for some specific types of the problems, the success of finding a solution is more than 90 percent. The results also show that the algorithm is efficient in terms of runtime when compared with a backtrack search algorithm.