By Yuji Matsumoto (auth.), Yasubumi Sakakibara, Satoshi Kobayashi, Kengo Sato, Tetsuro Nishino, Etsuji Tomita (eds.)

This publication constitutes the refereed lawsuits of the eighth overseas Colloquium on Grammatical Inference, ICGI 2006, held in Tokyo, Japan in September 2006.

The 25 revised complete papers and eight revised brief papers provided including 2 invited contributions have been rigorously reviewed and chosen from forty four submissions. the themes of the papers offered variety from theoretical result of studying algorithms to leading edge purposes of grammatical inference and from studying a number of fascinating sessions of formal grammars to purposes to ordinary language processing.

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Extra info for Grammatical Inference: Algorithms and Applications: 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006. Proceedings

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Theoretical Computer Science 185 (1997) 15–45 2. : A bibliographical study of grammatical inference. Pattern Recognition 38 (2005) 1332–1348 Identification in the Limit of Systematic-Noisy Languages 29 3. : Results of the abbadingo one DFA learning competition and a new evidence-driven state merging algorithm. LNCS 1433 (1998) 1–12 4. : Data complexity in Grammatical Inference. Number ISBN: 1-84628-171-7 in Advanced Information and Knowledge Processing. In: Data complexity in Pattern Recognition.

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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 context-free background knowledge. 1 Introduction Results in grammatical inference can usually be of use in several different domains. For instance progress in learning stochastic finite state machines and grammars has occurred because of efforts for computational biology [1,2], or speech recognition [3], or even document representation [4].

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