GoingToMeet

The conference seeks to provide a forum for presentation and discussion of original research papers on all aspects of grammatical inference including, but not limited to:

*Different models of grammar induction: e.g., learning from examples, learning using examples and queries, incremental versus non-incremental learning, distribution-free models of learning, learning under various distributional assumptions, learnability results, complexity results, characterizations of representational and search biases of grammar induction algorithms.
*Algorithms for induction of different classes of languages and automata: e.g., regular, context-free, and context-sensitive languages, interesting subclasses of the above under additional syntactic constraints, tree and graph grammars, picture grammars, multidimensional grammars, attributed grammars, parameterized models, etc.
*Theoretical and experimental analysis of different approaches to grammar induction including artificial neural networks, statistical methods, symbolic methods, information-theoretic approaches, minimum description length, complexity-theoretic approaches, heuristic methods, etc.
*Broader perspectives on grammar induction, e.g. acquisition of grammar in conjunction with language semantics, semantic constraints on grammars, language acquisition by situated agents and robots, acquisition of language constructs that describe objects and events in space and time, developmental and evolutionary constraints on language acquisition, statistical modelling of natural language, etc.

Historically the roots of grammatical inference have been in the modelling of first language acquisition by human infants: we especially invite submissions that address this theme, directly or indirectly.

The conference will include plenary and invited talks, software demonstrations and possibly poster presentations of accepted papers and tutorials. All plenary and invited papers will appear in the conference proceedings.