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.
Document type :
Preprints, Working Papers, ...
Complete list of metadatas

Cited literature [2 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01556243
Contributor : Oded Maler <>
Submitted on : Tuesday, July 4, 2017 - 6:32:36 PM
Last modification on : Friday, July 6, 2018 - 10:08:02 AM
Long-term archiving on : Friday, December 15, 2017 - 1:30:07 AM

File

bipartition-new.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01556243, version 1

Collections

Citation

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

Share

Metrics

Record views

264

Files downloads

151