Towards a general theory of action and time
Artificial Intelligence
A sufficient condition for backtrack-bounded search
Journal of the ACM (JACM)
A temporally oriented data model
ACM Transactions on Database Systems (TODS)
Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Tree clustering for constraint networks (research note)
Artificial Intelligence
Using temporal hierarchies to efficiently maintain large temporal databases
Journal of the ACM (JACM)
Artificial Intelligence - Special issue on knowledge representation
Artificial Intelligence
Effective solution of qualitative interval constraint problems
Artificial Intelligence
Reasoning about qualitative temporal information
Artificial Intelligence - Special volume on constraint-based reasoning
Complexity and algorithms for reasoning about time: a graph-theoretic approach
Journal of the ACM (JACM)
Decomposing constraint satisfaction problems using database techniques
Artificial Intelligence
A data model for processes based on relative time
Journal of Intelligent Information Systems
Combining qualitative and quantitative constraints in temporal reasoning
Artificial Intelligence
Processing disjunctions in temporal constraint networks
Artificial Intelligence
Formal semantics for time in databases
ACM Transactions on Database Systems (TODS)
Maintaining knowledge about temporal intervals
Communications of the ACM
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Incremental Implementation Model for Relational Databases with Transaction Time
IEEE Transactions on Knowledge and Data Engineering
A Uniform Model for Temporal Object-Oriented Databases
Proceedings of the Eighth International Conference on Data Engineering
Reasoning about change: time and causation from the standpoint of artificial intelligence
Reasoning about change: time and causation from the standpoint of artificial intelligence
A linear-programming approach to temporal reasoning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Temporal reasoning in process planning
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
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Temporal Constraint Satisfaction Problems (TCSP) is a well‐known approach for representing and processing temporal knowledge. Important properties of the knowledge can be inferred by computing the minimal networks of TCSPs. Consistency and feasible values are immediately obtained; computing solutions can be assisted. Yet, in general, computing the minimal network of a disjunctive TCSP is intractable. The minimal network approach requires computation of the full network in order to answer a query. In this paper we characterize TCSPs for which subsets of the minimal network can be computed without having to compute the whole network. The partial computation is enabled by decomposition of the problem into a tree of sub‐problems that share at most pairs of time points. Such decompositions are termed sim/2‐tree decompositions. For TCSPs that have sim/2‐tree decompositions, minimal constraints of input propositions can be computed by independent computations of the minimal networks of the sub‐problems at most twice. It is also shown that the sim/2‐tree characterization is a minimal set of conditions. The sim/2‐tree decomposition extends former results about decomposition of a TCSP into bi‐connected components. An algorithm for identifying a sim/2‐tree decomposition of a TCSP is provided as well. Finally, the sim/2‐tree decomposition is generalized in an inductive manner, which enables components of a decomposition to be further decomposed. For that purpose a model of Structured Temporal Constraint Satisfaction Problems (STCSP^{(n)},\ 0 \leq n), where STCSP^{(0)} is simply TCSP, STCSP^{(1)} is a set of STCSP^{(0)}s, and in general, STCSP^{(n)} for 1 \leq n is a set of STCSP^{(n-1)}s, is introduced.