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Behavioural Equivalence of Game Descriptions

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AI 2020: Advances in Artificial Intelligence (AI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12576))

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Abstract

Game description language is a logical language designed for General Game Playing. The language is highly expressive so that, in theory, all finite-state games with perfect information and deterministic actions can be described. However, a game can be described in different ways and the way of description can dramatically affect behaviour of general game players. This paper investigates the relationships of game models and game descriptions. We first introduce the concept of submodel bisimulation to filter out unreachable states while maintain the nature of a game. We then define equivalence of game descriptions in the sense that two game descriptions are equivalent if the described games behaviourally the same. The concept of game equivalency, which breaks through logical equivalency, sets a boundary for reformulation of game descriptions. Finally we use a well-known strategy game, Hex Game, to demonstrate how to verify equivalence of game descriptions.

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Notes

  1. 1.

    An easy example is that the property of reachability is not invariant under submodel bisimulation.

References

  1. Campbell, M., Hoane, A., Hsu, F.: Deep blue. Artif. Intell. 134(1), 57–83 (2002)

    Article  Google Scholar 

  2. Silver, D., et al.: Mastering the game of go with deep neural networks and tree search. Nature 529(7587), 484–489 (2016)

    Article  Google Scholar 

  3. Bowling, M., et al.: Heads-up limit hold’em poker is solved. Science 347(6218), 145–149 (2015)

    Article  Google Scholar 

  4. Silver, D., et al.: Mastering the game of go without human knowledge. Nature 550, 354–359 (2017)

    Article  Google Scholar 

  5. Pell, B.: A strategic metagame player for general chess-like games. Comput. Intell. 12(1), 177–198 (1996)

    Article  Google Scholar 

  6. Silver, D., et al.: A general reinforcement learning algorithm that masters chess, shogi, and go through self-play. Science 362(6419), 1140–1144 (2018)

    Article  MathSciNet  Google Scholar 

  7. Genesereth, M., Love, N., Pell, B.: General game playing: overview of the AAAI competition. AI Mag. 26(2), 62–72 (2005)

    Google Scholar 

  8. Genesereth, M., Thielscher, M.: General Game Playing. Morgan & Claypool Publishers (2014)

    Google Scholar 

  9. Love, N., Hinrichs, T., Genesereth, M.: General game playing: game description language specification. Tech. rep. Computer Science Department, Stanford University (2006)

    Google Scholar 

  10. Genesereth, M.M., Björnsson, Y.: The international general game playing competition. AI Mag. 34(2), 107–111 (2013)

    Article  Google Scholar 

  11. Swiechowski, M., Mandziuk, J.: Fast interpreter for logical reasoning in general game playing. J. Logic Comput. 24(5), 1071–1110 (2014)

    Article  MathSciNet  Google Scholar 

  12. Romero, J., Saffidine, A., Thielscher, M.: Solving the inferential frame problem in the general game description language. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, pp. 515–521. AAAI Press (2014)

    Google Scholar 

  13. Michon, J.A.: The game of jam: an isomorph of tic-tac-toe. Am. J. Psychol. 80(1), 137–140 (1967)

    Article  Google Scholar 

  14. Zhang, D., Thielscher, M.: A logic for reasoning about game strategies. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), pp. 1671–1677 (2015)

    Google Scholar 

  15. Zhang, D., Thielscher, M.: Representing and reasoning about game strategies. J. Philos. Logic 44(2), 203–236 (2015)

    Article  MathSciNet  Google Scholar 

  16. Zhang, D.: A logic for reasoning about game descriptions. In: AI 2018: Advances in Artificial Intelligence, pp. 38–50 (2018)

    Google Scholar 

  17. Gale, D.: The game of hex and the brouwer fixed-point theorem. Am. Math. Monthly 86(10), 818–827 (1979)

    Article  MathSciNet  Google Scholar 

  18. Blackburn, P., Rijke, M.D., Venema, Y.: Modal Logic. Cambridge University Press (2001)

    Google Scholar 

  19. Jiang, G., et al.: Game equivalence and bisimulation for game description language. In: PRICAI 2019: Trends in Artificial Intelligence, pp. 583–596 (2019)

    Google Scholar 

  20. Osborne, M.J., Rubinstein, A.: A Course in Game Theory. The MIT Press (1994)

    Google Scholar 

  21. Elmes, S., Reny, P.J.: On the strategic equivalence of extensive form games. J. Econ. Theo. 62(1), 1–23 (1994)

    Article  MathSciNet  Google Scholar 

  22. Bonanno, G.: Set-theoretic equivalence of extensive-form games. Int. J. Game Theo. 20(4), 429–447 (1992)

    Article  MathSciNet  Google Scholar 

  23. Zhang, H., Liu, D., Li, W.: Space-consistent game equivalence detection in general game playing. In: Cazenave, T., Winands, M.H.M., Edelkamp, S., Schiffel, S., Thielscher, M., Togelius, J. (eds.) CGW/GIGA -2015. CCIS, vol. 614, pp. 165–177. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39402-2_12

    Chapter  Google Scholar 

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Correspondence to Dongmo Zhang .

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Zhang, D. (2020). Behavioural Equivalence of Game Descriptions. In: Gallagher, M., Moustafa, N., Lakshika, E. (eds) AI 2020: Advances in Artificial Intelligence. AI 2020. Lecture Notes in Computer Science(), vol 12576. Springer, Cham. https://doi.org/10.1007/978-3-030-64984-5_24

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  • DOI: https://doi.org/10.1007/978-3-030-64984-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64983-8

  • Online ISBN: 978-3-030-64984-5

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