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Lecture Notes in Computer Science
Known algorithms for learning PDFA can only be shown to run in time polynomial in the so-called distinguishability µ of the target machine, besides the number of states and the usual accuracy and confidence parameters. We show that the dependence on µ is necessary for every algorithm whose structure resembles existing ones. As a technical tool, a new variant of Statistical Queries termed L∞-queries is defined. We show how these queries can be simulated from samples and observe that known PACdoi:10.1007/978-3-642-16108-7_17 fatcat:xknfxptpsfhvra7udyy4dn47mu