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Decision System Modelling for "Saboteur" using Heuristics and Means-Ends Analysis

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Published:21 January 2020Publication History

ABSTRACT

Saboteur is a card game played by several players. Players are divided into goldminers and saboteurs who prevents goldminers from finding gold. Each player knows his/her role, but he/she does not know who has the same role. Gold searching process starts by making a path of seven cards horizontally from a single point of reference to the gold card's position. Saboteur is classified as an incomplete information card game with mechanisms that requires complex decision making. This paper proposes an approach to model a decision system for Saboteur using Heuristics and Means-End Analysis. Implementation was purely done in Java language. To test it, we performed benchmarking for the proposed system against previous intelligent agent models. The result is much better.

References

  1. BoardGameGeek, "Saboteur," [Online]. Available: https://boardgamegeek.com/boardgame/9220/saboteur. [Accessed 1 May 2019].Google ScholarGoogle Scholar
  2. UltraBoardGames, "Saboteur Game Rules," [Online]. Available: https://www.ultraboardgames.com/saboteur/game-rules.php. [Accessed 1 May 2019].Google ScholarGoogle Scholar
  3. Krisnadi and S. Lukas, "Saboteur game modelling using means-ends analysis," in 2016 International Conference on Informatics and Computing (ICIC), Mataram, 2016.Google ScholarGoogle Scholar
  4. Whitehouse, "Monte Carlo Tree Search for games with Hidden Information and Uncertainty," 2014.Google ScholarGoogle Scholar
  5. M. Gołuński, R. Tomanek and P. Wasiewicz, "Modeling intelligent agent beliefs in a card game scenario," in Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2012, Wilga, 2012.Google ScholarGoogle Scholar

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  1. Decision System Modelling for "Saboteur" using Heuristics and Means-Ends Analysis

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    • Published in

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      ICAAI '19: Proceedings of the 3rd International Conference on Advances in Artificial Intelligence
      October 2019
      253 pages
      ISBN:9781450372534
      DOI:10.1145/3369114

      Copyright © 2019 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 21 January 2020

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