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2004
Springer

Learning Languages from Positive Data and Negative Counterexamples

12 years 8 months ago
Learning Languages from Positive Data and Negative Counterexamples
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the conjectures made by the learner. Several variants of this paradigm are considered that reflect different conditions/constraints on the type and size of negative counterexamples and on the time for obtaining them. In particular, we consider the models where 1) a learner gets the least negative counterexample; 2) the size of a negative counterexample must be bounded by the size of the positive data seen so far; 3) a counterexample can be delayed. Learning power, limitations of these models, relationships between them, as well as their relationships with classical paradigms for learning languages in the limit (without negative counterexamples) are explored. Several surprising results are obtained. In particular, for Gold’s model of learning requiring a learner to syntactically stabilize on correct conjecture...
Sanjay Jain, Efim B. Kinber
Added 15 Mar 2010
Updated 15 Mar 2010
Type Conference
Year 2004
Where ALT
Authors Sanjay Jain, Efim B. Kinber
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