Performance comparison between selected chess engines

Maciej Sojka

maciej.sojka@pollub.edu.pl
Politechnika Lubelska (Poland)

Abstract

Selected chess engines were compared to each other in terms of performance, using Lucas Chess. The list of engines was cut into three categories, depending on strength in ELO points. The point of this study is to find the strongest and the lightest engines in each category. Then, each category was tested using three different starting positions. White, black and overall wins were highlighted. At the same time, data of CPU and RAM usage of each engine was collected. A script was developed to print CPU and RAM usage of a specific process. Maximum and average percent of used CPU thread and RAM were highlighted. Chess engines with most amount of wins were, from weakest to strongest: Bikjump, Rybka and Stockfish. Least amount of system resources was consumed by: Cinnamon, Demolito and Critter.


Keywords:

chess, chess engines, performance comparison

A. Elo, The Proposed USCF Rating System, Its Development, Theory, and Applications, Chess Life 22 (1967) 242-247.
  Google Scholar

International Chess Federation - strona główna, https://www.fide.com/, [25.05.2022].
  Google Scholar

V. V. Vučković, Realization of the Chess Mate Solver Application., Yugoslav Journal of Operations Research 14 (2004) 273-288, https://doi.org/10.2298/YJOR0402273V.
DOI: https://doi.org/10.2298/YJOR0402273V   Google Scholar

W. B. Putra, L. Heryawan, Applying Alpha-beta Algorithm In A Chess Engine, Jurnal Teknosains UGM 6 (2016) 37-43.
DOI: https://doi.org/10.22146/teknosains.11380   Google Scholar

H. Zang, Z. Yu, X. Wan, Automated chess commentator powered by neural chess engine, arXiv (2019), https://doi.org/10.48550/arXiv.1909.10413.
DOI: https://doi.org/10.18653/v1/P19-1597   Google Scholar

M. Block, M. Bader, E. Tapia, M. Ramírez, K. Gunnarsson, E. Cuevas, D. Zaldivar, R. Rojas, Using Reinforcement Learning in Chess Engines, Research in Computing Science 35 (2008) 31-40.
  Google Scholar

N. Hesham, O. Abu-Elnasr, S. Elmougy, A New Action-Based Reasoning Approach for Playing Chess, Computers, Materials and Continua 69 (2021) 175-190.
DOI: https://doi.org/10.32604/cmc.2021.015168   Google Scholar

S. K. Bimonugroho, N. U. Maulidevi, A Hybrid Approach to Representing Chessboard using Bitboard and Compact Chessboard Representation, IOP Conference Series: Materials Science and Engineering 803 (2020), https://doi.org/10.1088/1757-899X/803/1/012018.
DOI: https://doi.org/10.1088/1757-899X/803/1/012018   Google Scholar

S. Maharaj, N. Polson, A. Turk, Chess AI: Competing Paradigms for Machine Intelligence, Entropy 24 (2022) 550, https://doi.org/10.48550/arXiv.2109.11602.
DOI: https://doi.org/10.3390/e24040550   Google Scholar

Strona internetowa programu Lucas Chess, https://lucaschess.pythonanywhere.com/home, [25.05.2022].
  Google Scholar

Magiczne tablice bitów - definicja, https://www.chessprogramming.org/Magic_Bitboards, [25.05.2022].
  Google Scholar

Leniwe SMP - definicja, https://www.chessprogramming.org/Lazy_SMP, [25.05.2022].
  Google Scholar

Okno aspiracji - definicja, https://www.chessprogramming.org/Aspiration_Windows, [25.05.2022].
  Google Scholar

Mistrzostwa ACCA World Computer Rapid Chess Championship 2016, https://www.chessprogramming.org/WCRCC_2016, [25.05.2022].
  Google Scholar

B. Steinbach, M. Werner, XBOOLE-CUDA -- Fast Boolean Operations on the GPU (2014).
  Google Scholar

Double bongcloud: why grandmasters are playing the worst move in chess, https://www.theguardian.com/sport/2021/mar/18/bongcloud-meme-opening-carlsen-nakamura, [20.06.2022]
  Google Scholar

Biblioteka psutil - dokumentacja, https://psutil.readthedocs.io/en/latest/, [25.05.2022].
  Google Scholar

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Published
2022-09-30

Cited by

Sojka, M. (2022). Performance comparison between selected chess engines. Journal of Computer Sciences Institute, 24, 228–235. https://doi.org/10.35784/jcsi.2975

Authors

Maciej Sojka 
maciej.sojka@pollub.edu.pl
Politechnika Lubelska Poland

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