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

Oded Maler (1)

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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.

Mots clés: Learring; Multi-criteria optimization; partial orders; parametric identification; binary search

Domaines: Informatique [cs]

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