Extending constraint logic programming for temporal reasoning
Annals of Mathematics and Artificial Intelligence
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Synthesis of efficient constraint-satisfaction programs
The Knowledge Engineering Review
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The design and implementation of constraint logic programming (CLP) languages over intervals is revisited. Instead of decomposing complex constraints in terms of simple primitive constraints as in CLP(BNR), complex constraints are manipulated as a whole, enabling more sophisticated narrowing procedures to be applied in the solver. This idea is embodied in a new CLP language Newton whose operational semantics is based on the notion of box-consistency, an approximation of arc-consistency, and whose implementation uses Newton interval method. Experimental results indicate that Newton outperforms existing languages by an order of magnitude and is competitive with some state-of-the-art tools on some standard benchmarks. Limitations of our current implementation and directions for further work are also identified.