A Polynomial Algorithm for the Inference of Context Free Languages
Alexander Clark, Rémi Eyraud and Amaury Habrard
In: 9th International Colloquium on Grammatical Inference (ICGI 2008), Saint Malo, France(2008).
We present a polynomial algorithm for the inductive inference of a
large class of context free languages, that includes all regular
The algorithm uses a representation which we call
Binary Feature Grammars based on a set of features, capable of
structured context free languages as well as some context sensitive
More precisely, we focus on a particular case of this representation
where the features correspond to contexts appearing in the language.
Using the paradigm of positive data and a membership oracle, we can
establish that all context free languages that satisfy two
constraints on the context distributions can be identified in the
limit by this approach. The polynomial time algorithm we propose is based on a
generalisation of distributional learning and uses the lattice of context
The formalism and the algorithm seem well suited to natural language
and in particular to the modelling of first language acquisition.