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Stockfish or Leela Chess Zero? A Comparison Against Endgame Tablebases

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Advances in Computer Games (ACG 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14528))

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Abstract

The game of chess has long been used as a benchmark for testing human creativity and intelligence. With the advent of powerful chess engines, such as Stockfish and Leela Chess Zero (Lc0), endgame studies have also become a tool for evaluating the capabilities of machine chess engines. In this work, we conduct a detailed study of Stockfish and Lc0, two leading chess engines with distinct methods of play, using chess endgames with varying numbers of remaining pieces. We evaluate the programs’ move decision errors when using only the raw policy network as well as when using a small amount of search. We provide insights into the strengths and weaknesses of Stockfish and Lc0 in handling complex endgame positions by exploring common mistakes and identifying interesting behaviours of the engines based on the position of the opponent’s last pawn remaining on the board.

Q.A. Sadmine and A. Husna—Equal contribution.

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Notes

  1. 1.

    https://www.chessprogramming.org/Forsyth-Edwards_Notation.

  2. 2.

    https://stockfishchess.org/blog/2022/stockfish-15-1.

  3. 3.

    https://github.com/LeelaChessZero/lc0/releases/tag/v0.29.0.

  4. 4.

    https://chess.fandom.com/wiki/Centipawn.

References

  1. Lc0 authors: lc0. https://lczero.org. Accessed 04 Mar 2023

  2. Lc0 authors: What is lc0? lczero.org/dev/wiki/what-is-lc0/. Accessed 04 Mar 2023

    Google Scholar 

  3. Lc0 authors: Win-draw-loss evaluation. lczero.org/blog/2020/04/wdl-head/. Accessed 24 Mar 2023

    Google Scholar 

  4. Stockfish authors: Stockfish. https://stockfishchess.org. Accessed 04 Mar 2023

  5. Ballicora, M.: Gaviota. sites.google.com/site/gaviotachessengine/Home/ endgame-tablebases-1. Accessed 27 Feb 2023

    Google Scholar 

  6. Coulom, R.: Efficient selectivity and backup operators in Monte-Carlo tree search. In: International Conference on Computers and Games, pp. 72–83. Springer (2006)

    Google Scholar 

  7. Edwards, D.J., Hart, T.: The alpha-beta heuristic. Tech. Rep. AIM-30, MIT (1961)

    Google Scholar 

  8. Forsten, H.: Purpose of the moves left head. https://github.com/Leela ChessZero/lc0/pull/961#issuecomment-587112109. Accessed 24 Mar 2023

  9. Haque, R., Wei, T.H., Müller, M.: On the road to perfection? evaluating leela chess zero against endgame tablebases. In: Advances in Computer Games: 17th International Conference, ACG 2021, Virtual Event, November 23–25, 2021, Revised Selected Papers, pp. 142–152. Springer (2022)

    Google Scholar 

  10. Heinz, E.A.: Extended futility pruning. ICGA J. 21(2), 75–83 (1998)

    Google Scholar 

  11. Kryukov, K.: Number of unique legal positions in chess endgames (2014). http://kirillkryukov.com/chess/nulp/. Accessed 26 Feb 2023

  12. Lassabe, N., Sanchez, S., Luga, H., Duthen, Y.: Genetically programmed strategies for chess endgame. In: Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation, pp. 831–838 (2006)

    Google Scholar 

  13. de Man, R., Guo, B.: Syzygy endgame tablebases. syzygy-tables.info/. Accessed 06 Mar 2023

    Google Scholar 

  14. de Man, R.: Syzygy. https://github.com/syzygy1/tb. Accessed 08 Mar 2023

  15. McGrath, T., Kapishnikov, A., Tomašev, N., Pearce, A., Wattenberg, M., Hassabis, D., Kim, B., Paquet, U., Kramnik, V.: Acquisition of chess knowledge in alphazero. Proc. Natl. Acad. Sci. 119(47), e2206625119 (2022)

    Article  MathSciNet  Google Scholar 

  16. Nasu, Y.: Efficiently updatable neural-network-based evaluation functions for computer shogi. The 28th World Computer Shogi Championship Appeal Document 185 (2018)

    Google Scholar 

  17. Romein, J.W., Bal, H.E.: Awari is solved. ICGA J. 25(3), 162–165 (2002)

    Article  Google Scholar 

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

    Google Scholar 

  19. Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., 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 

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Authors and Affiliations

  1. University of Alberta, Edmonton, Canada

    Quazi Asif Sadmine, Asmaul Husna & Martin Müller

Authors
  1. Quazi Asif Sadmine
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  2. Asmaul Husna
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  3. Martin Müller
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Corresponding author

Correspondence to Asmaul Husna .

Editor information

Editors and Affiliations

  1. University of Siegen, Siegen, Germany

    Michael Hartisch

  2. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Chu-Hsuan Hsueh

  3. University of Alberta, Edmonton, AB, Canada

    Jonathan Schaeffer

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Sadmine, Q.A., Husna, A., Müller, M. (2024). Stockfish or Leela Chess Zero? A Comparison Against Endgame Tablebases. In: Hartisch, M., Hsueh, CH., Schaeffer, J. (eds) Advances in Computer Games. ACG 2023. Lecture Notes in Computer Science, vol 14528. Springer, Cham. https://doi.org/10.1007/978-3-031-54968-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-54968-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-54967-0

  • Online ISBN: 978-3-031-54968-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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