Solving Crossword Puzzles Using Extended Potts Model

Authors:
Kazuki Jimbo;Hiroya Takamura;Manabu Okumura
Affiliations:
Department of Computer Science, Tokyo Institute of Technology,;Precision and Intelligence Laboratory, Tokyo Institute of Technology,;Precision and Intelligence Laboratory, Tokyo Institute of Technology,
Venue:
New Frontiers in Artificial Intelligence
Year:
2009

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Abstract

Solving crossword puzzles by computers is a challenging task in artificial intelligence. It requires logical inference and association as well as vocabulary and common sense knowledge. For this task, we present an extension of the Potts model. This model can incorporate various clues for solving puzzles and require less computational cost compared with other existing models.