דנה פיסמן

אקדמי בכיר

Learning regular omega languages

Dana Angluin, Dana Fisman

We provide an algorithm for learning an unknown regular set of infinite words, using membership and equivalence queries. Three variations of the algorithm learn three different canonical representations of omega regular languages, using the notion of families of dfas. One is of size similar to L$, a dfa representation recently learned using L∗ [7]. The second is based on the syntactic forc, introduced in [14]. The third is introduced herein. We show that the second can be exponentially smaller than the first, and the third is at most as large as the first two, with up to a quadratic saving with respect to the second.

שפת פרסום אנגלית
דפים 125-139
סטטוס פרסום פורסם - 01.01.2014

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science
גישה למסמך
10.1007/978-3-319-11662-4_10
קבצים וקישורים אחרים
Link to publication in Scopus