Iterative Learning from Texts and Counterexamples Using Additional Information

Abstract. A variant of iterative learning in the limit (cf. [LZ96]) is studied when a learner gets negative examples refuting conjectures containing data in excess of the target language and uses additional information of the following four types: a) memorizing up to n input elements seen so far; b) up to n feedback memberships queries (testing if an item is a member of the input seen so far); c) the number of input elements seen so far; d) the maximal element of the input seen so far. We explore how additional information available to such learners (defined and studied in [JK07]) may help. In particular, we show that adding the maximal element or the number of elements seen so far helps such learners to infer any indexed class of languages class-preservingly (using a descriptive numbering defining the class) — as it is proved in [JK07], this is not possible without using additional information. We also study how, in the given context, different types of additional information far...

• Type: Conference
• Year: 2009
• Where: ALT
• Authors: Sanjay Jain, Efim B. Kinber
• Keywords: Additional Information, ALT 2009, Input Elements, Machine Learning, Maximal Element