Chess Engine Research Articles

The 19th Top Chess Engine Championship, TCEC19

TCEC19 was the 18th season of the Top Chess Engine Championship and ran from August 6th to October 16th, 2020. TCEC has become the largest Open Computer Chess Championship. It attracts the best engines in the field and provides an opportunity for a comparative analysis of the Shannon-AB and the new Neural-Network engines’ styles of play. STOCKFISH retained the Grand Champion title with +9 in another exciting Superfinal, but only because it took on 'NN' technology 'just in time'. These two engines have dominated the field for the last eight TCEC seasons now. The attached files at http://centaur.reading.ac.uk/93815 provide the 726 games with engine PVs, the detail on them, some summary statistics and the completion to mate of the wins. Bonus matches put these two engines' performance in a valuable context of STOCKFISH_CLASSICAL and KOMODO.

The 17th Top Chess Engine Championship, TCEC17

TCEC17 was the 17th season of the Top Chess Engine Championship and ran from January 2nd to 21st April, 2020. TCEC has become the largest Open Computer Chess Championship. It attracts the best engines in the field and provides an opportunity for a comparative analysis of the Shannon-AB and the new Neural-Network engines’ styles of play. LEELA CHESS ZERO took the Grand Champion title from STOCKFISH again with +5 in an exciting Superfinal. The attached files at http://centaur.reading.ac.uk/89999 provide the 1300 games with engine PVs, the detail on them, some summary statistics and the completion to mate of the wins.

The SSDF Rating List, 2020-07, in memoriam Tony Hedlund

This is the Chess Engine Rating list of 2020-07 from Svenska schackdatorforeningen, the Swedish Chess Computer Association. It is dedicated to the late Tony Hedlund, a leading contributor to SSDF who also managed its database of games. SSDF has produced the list for 23 years. Here we supply the 'Selected 50' subset with headline notes on each engine. SSDF's 2020-07 narrative, top 50 and long lists (both with match details) may also be downloaded from here.

Cognitive Performance in the Home Office - Evidence from Professional Chess

During the recent COVID-19 pandemic, traditional (offline) chess tournaments were prohibited and instead held online. We exploit this as a unique setting to assess the impact of moving offline tasks online on the cognitive performance of individuals. We use the Artificial Intelligence embodied in a powerful chess engine to assess the quality of chess moves and associated errors. Using within-player comparisons, we find a statistically and economically significant decrease in performance when competing online compared to competing offline. Our results suggest that teleworking might have adverse effects on workers performing cognitive tasks.

On the Causes and Consequences of Deviations from Rational Behavior

This paper presents a novel approach to analyze human decision-making that involves comparing the behavior of professional chess players relative to a computational benchmark of cognitively bounded rationality. This benchmark is constructed using algorithms of modern chess engines and allows investigating behavior at the level of individual move-by-move observations, thus representing a natural benchmark for computationally bounded optimization. The analysis delivers novel insights by isolating deviations from this benchmark of bounded rationality as well as their causes and consequences for performance. The findings document the existence of several distinct dimensions of behavioral deviations, which are related to asymmetric positional evaluation in terms of losses and gains, time pressure, fatigue, and complexity. The results also document that deviations from the benchmark do not necessarily entail worse performance. Faster decisions are associated with more frequent deviations from the benchmark, yet they are also associated with better performance. The findings are consistent with an important influence of intuition and experience, thereby shedding new light on the recent debate about computational rationality in cognitive processes.

The SSDF Chess Engine Rating List, 2019-07

This is the Chess Engine Rating list of 2019-07 from Svenska schackdatorforeningen, the Swedish Chess Computer Association. SSDF has produced the list for 22 years. Here we supply the 'Selected 50' subset with headline notes on each engine. SSDF's 2019-07 long list and hw/change logs may also be downloaded from here.

TCEC15: The 15th Top Chess Engine Championship

TCEC15: The 15th Top Chess Engine Championship

TCEC14: The 14th Top Chess Engine Championship

TCEC14: The 14th Top Chess Engine Championship

Yüz İfadesine Göre Satranç Oynayan Robot: Çolak

In this study, it is aimed to play chess by sending moves to Stockfish chess engine according to emotion intensities of Arduino Braccio Robot arm's opponent's facial features. Within the scope of the application, it is necessary to gain the necessary skills for the recognition of the environment, the visual system that can monitor the competitor and the realization of the movements. In order to carry out the necessary recognition and movement procedures, a software has been prepared to be run on personal computers. The commands to be given to the robot arm are sent via Arduino Yun. The status information of the arm, the environment and the opponent will be placed parallel to the chessboard and parallel to the opponent and provided with two cameras which will work in harmony with Arduino. The aim of the study is to build a robotic arm that plays chess completely with the necessary algorithms and capabilities. It is shown that it is possible to create such a system by performing necessary kinetic and image processing studies.

TCEC13: The 13th top chess engine championship

TCEC15 was the 15th season of the Top Chess Engine Championship and ran from March 5th to May 28th, 2019. TCEC has become the largest Open Computer Chess Championship. It attracts the best engines in the field and provides an opportunity for absolute and comparative analysis of the participating engines in a computational experiment. Once again, the final offered a contrast of playing styles between neural-network engine LEELA CHESS ZERO and STOCKFISH. This time, the ‘new architecture’ LC0 won, 53½-46½, making their ‘TCEC Sufi’ score 103-97 to LC0. Again, KOMODO was third. The attached files at http://centaur.reading.ac.uk/83156/ provide the 808 games with engine PVs, the detail on them and some summary statistics. The decisive games of Divisions 1 and P, and of the Superfinal have been played out by FRITZ17 at depth 24 to mate to enable and benchmark endgame practice.

The SSDF Chess Engine Rating List 2019-02

This is the Chess Engine Rating list of 2019-02 from Svenska schackdatorforeningen, the Swedish Chess Computer Association. SSDF has produced the list for 21 years. Here we supply the 'Selected 50' subset with headline notes on each engine. SSDF's 2019-02 narrative and long list may also be downloaded from here.

TCEC Cup 2

This is a report of the 'TCEC Cup 2' computational experiment, the second TCEC knockout event and the second major part of TCEC’s 14th season. It featured the best 32 engines of the ‘TCEC 14’ league event and the games were held at Blitz tempo. The different format called for different optimal settings in the engines, thereby enabling a comparison with performance at slower tempi. This event made history: the first major trophy win by a 'NN' Neural Network chess engine, LEELA CHESS ZERO, even though relatively disadvantaged by the faster tempo. All decisive games in the supplementary data have been played out by FRITZ17 at search depth 24 to benchmark endgame practice.

TCEC12: The 12th Top Chess Engine Championship

TCEC12: The 12th Top Chess Engine Championship

The SSDF Chess Engine Rating List 2018-10

This is the Chess Engine Rating list of 2018-10 from Svenska schackdatorforeningen, the Swedish Chess Computer Association. SSDF has produced the list for 21 years. Here we supply the 'Selected 50' subset with headline notes on each engine. The full details of the 2018-10 may also be downloaded from here.

TCEC11: the 11th Top Chess Engine Championship

TCEC11: the 11th Top Chess Engine Championship

TCEC10: The 10th Top Chess Engine Championship

TCEC10: The 10th Top Chess Engine Championship

On the Creation of a Chess-AI-Inspired Problem-Specific Optimizer for the Pseudo Two-Dimensional Battery Model Using Neural Networks

In this work, an artificial intelligence based optimization analysis is done using the porous electrode pseudo two-dimensional (P2D) lithium-ion battery model. Due to the nonlinearity and large parameter space of the physics-based model, parameter calibration is often an expensive and difficult task. Several classes of optimizers are tested under ideal conditions. Using artificial neural networks, a hybrid optimization scheme inspired by the neural network-based chess engine DeepChess is proposed that can significantly improve the converged optimization result, outperforming a genetic algorithm and polishing optimizer pair by 10-fold and outperforming a random initial guess by 30-fold. This initial guess creation technique demonstrates significant improvements on accurate identification of model parameters compared to conventional methods. Accurate parameter identification is of paramount importance when using sophisticated models in control applications.

Indoor Air Quality and Cognitive Performance

This paper studies the causal impact of indoor air quality on the cognitive performance of individuals using data from official chess tournaments. We use a chess engine to evaluate the quality of moves made by individual players and merge this information with measures of air quality inside the tournament venue. The results show that poor indoor air quality hampers cognitive performance significantly. We find that an increase in the indoor concentration of fine particulate matter (PM2.5) by 10 μg/m3 increases a player's probability of making an erroneous move by 26.3%. The impact increases in both magnitude and statistical significance with rising time pressure. The effect of the indoor concentration of carbon dioxide (CO2) is smaller and only matters during phases of the game when decisions are taken under high time stress. Exploiting temporal as well as spatial variation in outdoor pollution, we provide evidence suggesting a short-term and transitory effect of fine particulate matter on cognition.

Design and Implementation of a Computer Vision System for an Autonomous Chess-Playing Robot

This work describes a mechatronic system composed by a robot arm that can play chess autonomously. The system is based on an industrial-grade robot manipulator, a computer vision system, and an open source chess engine. Classification algorithms were implemented in order to detect whether a given chessboard square is occupied, and in that case, if the piece is black or white. Such algorithms were compared in terms of their complexity of implementation, execution time and accuracy of predictions. To achieve an uniform illumination of the chessboard, a theoretical model of an LED illuminance curve was used to find the best orientation for each diode using a genetic algorithm. Both the support base for the LEDs and the chess pieces were made using a 3D printer. This implementation demonstrates the capabilities of the proposed vision-based system, whose complexity can be increased in the future for a number of applications.

The SSDF chess engine rating list

The SSDF chess engine rating list