Sorting by decision trees with hypotheses (extended abstract)

Mohammad Azad, Igor Chikalov, Shahid Hussain, Mikhail Moshkov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we consider decision trees that use both queries based on one attribute each and queries based on hypotheses about values of all attributes. Such decision trees are similar to ones studied in exact learning, where not only membership but also equivalence queries are allowed. For n = 3,..., 6, we compare decision trees based on various combinations of attributes and hypotheses for sorting n pairwise different elements from linearly ordered set.
Original languageEnglish (US)
Title of host publication29th International Workshop on Concurrency, Specification and Programming, CS and P 2021
PublisherCEUR-WS
Pages126-130
Number of pages5
StatePublished - Jan 1 2021

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