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Title: A risk driven state merging algorithm for learning DFAs
Authors: Spina, Sandro
Keywords: Machine learning
Computer algorithms
Statistical matching
Heuristic algorithms
Issue Date: 2003
Publisher: University of Malta. Faculty of ICT
Citation: Spina, S. (2003). A risk driven state merging algorithm for learning DFAs. 1st Computer Science Annual Workshop (CSAW’03), Msida. 99-102.
Abstract: When humans efficiently infer complex functions from a relatively few but well- chosen examples, something beyond exhaustive search must probably be at work. Different heuristics are often made use of during this learning process in order to efficiently infer target functions. Our current research focuses on different heuristics through which regular grammars can be efficiently inferred from a minimal amount of examples. A brief introduction to the theory of grammatical inference is given, followed by a brief discussion of the current state of the art in automata learning and methods currently under development which we believe can improve automata learning when using sparse data.
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