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Ten Open Problems in Grammatical Inference
, 2006
"... We propose 10 different open problems in the field of grammatical inference. In all cases, problems are theoretically oriented but correspond to practical questions. They cover the areas of polynomial learning models, learning from ordered alphabets, learning deterministic Pomdps, learning negotiati ..."
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We propose 10 different open problems in the field of grammatical inference. In all cases, problems are theoretically oriented but correspond to practical questions. They cover the areas of polynomial learning models, learning from ordered alphabets, learning deterministic Pomdps, learning negotiation processes, learning from contextfree background knowledge.
Inference of ωlanguages from prefixes
 Theoretical Computer Science
, 2004
"... Abstract. Büchi automata are used to recognize languages of infinite words. Such languages have been introduced to describe the behavior of real time systems or infinite games. The question of inferring them from infinite examples has already been studied, but it may seem more reasonable to believe ..."
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Abstract. Büchi automata are used to recognize languages of infinite words. Such languages have been introduced to describe the behavior of real time systems or infinite games. The question of inferring them from infinite examples has already been studied, but it may seem more reasonable to believe that the data from which we want to learn is a set of finite words, namely the prefixes of accepted or rejected infinite words. We describe the problems of identification in the limit and polynomial identification in the limit from given data associated to different interpretations of these prefixes: a positive prefix is universal (respectively existential) when all the infinite words of which it is a prefix are in the language (respectively when at least one is) ; the same applies to the negative prefixes. We prove that the classes of regular ωlanguages (those recognized by Büchi automata) and of deterministic ωlanguages (those recognized by deterministic Büchi automata) are not identifiable in the limit, whichever interpretation for the prefixes is taken. We give a polynomial algorithm that identifies the class of safe languages from positive existential prefixes and negative universal prefixes. We show that this class is maximal for polynomial identification in the limit from given data, in the sense that no superclass can even be identified in the limit. 1
Complexity and reduction issues in grammatical inference
, 2005
"... Grammatical inference deals with learning grammars or automata from different textual informations. A general paradigm allowing us to describe the convergence of the process is that of identification in the limit. When trying to combine this paradigm with complexity issues, problems arise. We revisi ..."
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Grammatical inference deals with learning grammars or automata from different textual informations. A general paradigm allowing us to describe the convergence of the process is that of identification in the limit. When trying to combine this paradigm with complexity issues, problems arise. We revisit identification in the limit from a (slightly) categorial perspective, and formalise a reduction technique between problems that allows to refine previous results.