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人工知能学会論文誌
Vol. 29 (2014) No. 1 論文特集「知的対話システム」,「近未来チャレンジ 2012」,一般論文,2013年度大会速報論文特集 p. 182-187

記事言語:

http://doi.org/10.1527/tjsai.29.182

速報論文

SLIM is an LMNtal runtime. LMNtal is a programming and modeling language based on hierarchical graph rewriting. SLIM features automata-based LTL model checking that is one of the methods to solve accepting cycle search problems. Parallel search algorithms OWCTY and MAP used by SLIM generate a large number of states for problems having and accepting cycles. Moreover, they have a problem that performance seriously falls for particular problems. We propose a new algorithm that combines MAP and Nested DFS to remove states for problems including accepting cycles. We experimented the algorithm and confirmed improvements both in performance and scalability.

Copyright © 人工知能学会 2014

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