1Institute of Engineering & Technology, Department of Computer Engineering, Devi Ahilya University, Khandwa Road, Indore 452017, M.P. India.
2School of Computer Engineering, Nanyang Technological University, Block N4-2a-32, 50, Nanyang Avenue, Singapore 639798.
*E-mail: suresh.jain@rediffmail.com
**E-mail: asnarendra@ntu.edu.sg, nscmp@lycos.com
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Incremental learning algorithms play an important role in situations where all the training examples are not available to the learner at the start and they are suitable for online learning tasks. In this paper, we present an incremental algorithm for identifying the target deterministic finite automaton (DFA) using augmented prefix tree automaton (APTA). Proposed incremental APTA admissible merge (IAAM) algorithm extends the sequential AAM algorithm to an incremental setting. Our algorithm correctly identifies the target DFA in the limit using characteristic sample.
Learning Theory, Learning by Examples, Incremental Learning, Language Inference, Computational Learning, Learning of Finite Automaton
