Solving Sudoku with Consistency: A Visual and Interactive Approach

Autor: Christian Bessiere, Robert J. Woodward, Ian S. Howell, Berthe Y. Choueiry
Přispěvatelé: Constraint Systems Laboratory, University of Nebraska [Lincoln], University of Nebraska System-University of Nebraska System, Agents, Apprentissage, Contraintes (COCONUT), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: 27th International Joint Conference on Artificial Intelligence
IJCAI: International Joint Conference on Artificial Intelligence
IJCAI: International Joint Conference on Artificial Intelligence, Jul 2018, Stockholm, Sweden. pp.5829-5831, ⟨10.24963/ijcai.2018/852⟩
IJCAI
DOI: 10.24963/ijcai.2018/852⟩
Popis: We describe an online, interactive system with a graphical interface to illustrate the power and operation of consistency algorithms in a friendly and popular context, namely, solving Sudoku puzzles. Our tool implements algorithms for enforcing five (domain-based) consistency properties on binary and non-binary constraint models. Our tool is useful for research, education, and outreach. From a scientific standpoint, we propose a new consistency property that can solve the hardest known 9×9 Sudoku instances without search, but leave open the question of the lowest level of consistency needed to solve every 9×9 Sudoku puzzle. We have used the current tool and its predecessor in the classroom to introduce students to modeling problems with constraints, explain consistency properties, and illustrate the operations of constraint propagation and lookahead. Finally, we have also used this tool during outreach activities to demystify AI to children and the general public and show them how computers think.
Databáze: OpenAIRE