Solving Logical Puzzles in DisCoCirc
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Finding a full solution to logical puzzles, from parsing the text to arriving at the answer, forms an active area of research in artificial intelligence. In this paper, we address an initial subset of these puzzles that take the form of constraint satisfaction problems, providing a method for solving them by encoding the puzzle meaning as a relation informed by the individual sentences that make up the puzzle text. To build this relation from the text we make use of a diagrammatic, distributional compositional framework called DisCoCirc. We then show that the puzzle solution can be extracted from this encoding with minimal extra work, as the logical form of the puzzle is modelled and evaluated as the meaning encoding is computed.
Abstract
Finding a full solution to logical puzzles, from parsing the text to arriving at the answer, forms an active area of research in artificial intelligence. In this paper, we address an initial subset of these puzzles that take the form of constraint satisfaction problems, providing a method for solving them by encoding the puzzle meaning as a relation informed by the individual sentences that make up the puzzle text. To build this relation from the text we make use of a diagrammatic, distributional compositional framework called DisCoCirc. We then show that the puzzle solution can be extracted from this encoding with minimal extra work, as the logical form of the puzzle is modelled and evaluated as the meaning encoding is computed.
참고문헌 (25)
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