Towards a general theory of action and time
Artificial Intelligence
Artificial Intelligence
Constraint propagation algorithms for temporal reasoning: a revised report
Readings in qualitative reasoning about physical systems
Exact and approximate reasoning about temporal relations
Computational Intelligence
Proceedings of the first international conference on Principles of knowledge representation and reasoning
Maintaining knowledge about temporal intervals
Communications of the ACM
Planning using a temporal world model
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Experimental evaluation of preprocessing techniques in constraint satisfaction problems
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Approximation algorithms for temporal reasoning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Managing efficiently temporal relations through indexed spanning trees
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
A syntactical approach to qualitative constraint networks merging
LPAR'10 Proceedings of the 17th international conference on Logic for programming, artificial intelligence, and reasoning
Temporal query processing with indefinite information
Artificial Intelligence in Medicine
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Interval and point algebras have been proposed for representing qualitative temporal information about the relationships between pairs of intervals and pairs of points, respectively. In this paper, we address two related reasoning tasks that arise in these algebras: Given (possibly indefinite) knowledge of the relationships between some intervals or points, (1) find one or more scenarios that are consistent with the information provided, and (2) find all the feasible relations between every pair of intervals or points. Solutions to these problems have applications in natural language processing, planning, and a knowledge representation language. We define computationally efficient procedures for solving these tasks for the point algebra and for a corresponding subset of the interval algebra. Our algorithms are marked improvements over the previously known algorithms. We also show how the results for the point algebra aid in the design of a backtracking algorithm for the full interval algebra that is useful in practice.