Learning Monotone Partitions of Partially-Ordered Domains (Work in Progress)

Abstract : We present an algorithm for learning the boundary between an upward-closed set X and its downward-closed complement. The algorithm selects sampling points for which it submits membership queries x ∈ X. Based on the answers and relying on monotonicity, it constructs an approximation of the boundary. The algorithm generalizes binary search on the continuum from one-dimensional (and linearly-ordered) domains to multi-dimensional (and partially-ordered) ones. Applications include the approximation of Pareto fronts in multi-criteria optimization and parameter synthesis for predicates where the influence of parameters is monotone.
Type de document :
Pré-publication, Document de travail
2017
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https://hal.archives-ouvertes.fr/hal-01556243
Contributeur : Oded Maler <>
Soumis le : mardi 4 juillet 2017 - 18:32:36
Dernière modification le : dimanche 9 juillet 2017 - 01:02:30

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bipartition-new.pdf
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  • HAL Id : hal-01556243, version 1

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Oded Maler. Learning Monotone Partitions of Partially-Ordered Domains (Work in Progress). 2017. <hal-01556243>

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