In this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle.
|Number of pages||15|
|Journal||Theory and Practice of Logic Programming|
|Publication status||Published - Jul 2013|
|Event||29th International Conference on Logic Programming - Istanbul, Turkey, Istanbul|
Duration: 24 Jul 2013 → 29 Jul 2013