dc.contributor.author Podnieks, Karlis dc.date.accessioned 2015-11-28T17:49:23Z dc.date.available 2015-11-28T17:49:23Z dc.date.issued 1977 dc.identifier.citation K. Podnieks. Probabilistic programs synthesis. In: Theory of Algorithms and Programs, Vol. 3, Latvia State University, 1977, pp. 57–88 en_US dc.identifier.uri https://dspace.lu.lv/dspace/handle/7/31217 dc.description.abstract The following model of inductive inference is considered. Arbitrary numbering tau = {tau_0, tau_1, tau_2, ... } of total functions N->N is fixed. A "black box" outputs the values f(0), f(1), ..., f(m), ... of some function f from the numbering tau. Processing these values by some algorithm (a strategy) F we try to identify a tau-index of f (i.e. a number n such that f = tau_n). Strategy F outputs hypotheses h_0, h_1, ..., h_m, ... If lim h_m = n and tau_n = f, we say that F identifies in the limit tau-index of f. The complexity of identification is measured by the number of mindchanges, i.e. by F_tau(f) = card{m | h_m <> h_{m+1} }. One can verify easily that for any numbering tau there exists a deterministic strategy F such that F_tau(tau_n) <= n for all n. This estimate is exact. In the current paper the corresponding exact estimate ln n + o(log n) is proved for probabilistic strategies. en_US dc.language.iso rus en_US dc.publisher Latvia State University en_US dc.rights info:eu-repo/semantics/openAccess en_US dc.subject machine learning en_US dc.subject inductive inference en_US dc.subject program synthesis en_US dc.title Probabilistic program synthesis en_US dc.type info:eu-repo/semantics/article en_US
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