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Search Techniques for Non-Linear Constraint Satisfaction Problems with Inequalities

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Advances in Artificial Intelligence (Canadian AI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2056))

Abstract

In recent years, interval constraint-based solvers have shown their ability to efficiently solve challenging non-linear real constraint problems. However, most of the working systems limit themselves to delivering point-wise solutions with an arbitrary accuracy. This works well for equalities, or for inequalities stated for specifying tolerances, but less well when the inequalities express a set of equally relevant choices, as for example the possible moving areas for a mobile robot. In that case it is desirable to cover the large number of point-wise alternatives expressed by the constraints using a reduced number of sets, as interval boxes. Several authors [2,1,7] have proposed set covering algorithms specific to inequality systems. In this paper we propose a lookahead backtracking algorithm for inequality and mixed equality/inequality constraints. The proposed technique combines a set covering strategy for inequalities with classical interval search techniques for equalities. This allows for a more compact representation of the solution set and improves efficiency.

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References

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© 2001 Springer-Verlag Berlin Heidelberg

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Silaghi, MC., Sam-Haroud, D., Faltings, B. (2001). Search Techniques for Non-Linear Constraint Satisfaction Problems with Inequalities. In: Stroulia, E., Matwin, S. (eds) Advances in Artificial Intelligence. Canadian AI 2001. Lecture Notes in Computer Science(), vol 2056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45153-6_18

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  • DOI: https://doi.org/10.1007/3-540-45153-6_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42144-3

  • Online ISBN: 978-3-540-45153-2

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