Learning to automatically solve logic grid puzzles

Arindam Mitra, Chitta Baral

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Logic grid puzzle is a genre of logic puzzles in which we are given (in a natural language) a scenario, the object to be deduced and certain clues. The reader has to figure out the solution using the clues provided and some generic domain constraints. In this paper, we present a system, Logicia, that takes a logic grid puzzle and the set of elements in the puzzle and tries to solve it by translating it to the knowledge representation and reasoning language of Answer Set Programming (ASP) and then using an ASP solver. The translation to ASP involves extraction of entities and their relations from the clues. For that we use a novel learning based approach which uses varied supervision, including the entities present in a clue and the expected representation of a clue in ASP. Our system, LOGICIA, learns to automatically translate a clue with 81.11% accuracy and is able to solve 71% of the problems of a corpus. This is the first learning system that can solve logic grid puzzles described in natural language in a fully automated manner. The code and the data will be made publicly available at http://bioai. lab. asu.edu/logicgridpuzzles.

Original languageEnglish (US)
Title of host publicationConference Proceedings - EMNLP 2015
Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Pages1023-1033
Number of pages11
ISBN (Electronic)9781941643327
DOIs
StatePublished - Jan 1 2015
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
Duration: Sep 17 2015Sep 21 2015

Publication series

NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Other

OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2015
CountryPortugal
CityLisbon
Period9/17/159/21/15

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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  • Cite this

    Mitra, A., & Baral, C. (2015). Learning to automatically solve logic grid puzzles. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 1023-1033). (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1118