TCEC14: the 14th top chess engine championship

TCEC14 was the 14th season of the Top Chess Engine Championship and ran from December 14th 2018 to 23rd February 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. This time, the neural-network engine LEELA CHESS ZERO made the final and only narrowly lost to STOCKFISH. KOMODO was third in the Premier Division. The attached files provide the 868 games, the detail on them and some summary statistics. The Superfinal games have been played out to mate by FRITZ17 searching to depth 24

TCEC13: the 13th Top Chess Engine Championship

TCEC13 was the 13th season of the Top Chess Engine Championship and ran from August 3rd to November 7th, 2018. 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. This now includes two rapidly evolving non-Shannon ‘neural network’ engines, DEUS X and LEELA CHESS ZERO, which echo ALPHAZERO’s mould-breaking appearance. This time, there were 772 games across the tiers of the event. STOCKFISH beat KOMODO in the final with HOUDINI in third. The TCEC13 files provide the detailed PV-analyses of the engines themselves. The games and statistical analyses are available here: the decisive Superfinal games are played out to mate by FRITZ17 searching to depth 24

Recognition of positional motifs in chess positions

In this diploma thesis, we first prepared a programme for automatic recognising of positional motifs. We focused on recognising of pawn structures, such as isolated pawns, passed pawns, doubled pawns, backward pawns, pawn chains, and pawn islands. The programme was implemented in the Python programming language with the help of the library python-chess that enables simple use of bitboards. The developed programme could be used for automatic annotation of chess games. Then, we addressed the problem of searching for chess positions with similar content. The automatic recognising of pawn structures was integrated into the programme as a component, wherein the programme is able to find chess positions with similar content, taking into account the characteristics of pawn structures on a chessboard as well. We used techniques for information retrieval from text documents, using an open-source library Apache Lucene. Partly, the development took place in the environment Jupyter Notebook, which enables simple visualization of chess positions. The search of positions with similar content can be used for automatic preparation of chess trainings, whereby the job of chess trainers can be made easier. We could improve the algorithm for searching similar positions by recognising dynamic, tactical motifs. The competence of the programme for discovering positions with similar content was confirmed by a survey carried out among chess players

Recognition of positional motifs in chess positions

In this diploma thesis, we first prepared a programme for automatic recognising of positional motifs. We focused on recognising of pawn structures, such as isolated pawns, passed pawns, doubled pawns, backward pawns, pawn chains, and pawn islands. The programme was implemented in the Python programming language with the help of the library python-chess that enables simple use of bitboards. The developed programme could be used for automatic annotation of chess games. Then, we addressed the problem of searching for chess positions with similar content. The automatic recognising of pawn structures was integrated into the programme as a component, wherein the programme is able to find chess positions with similar content, taking into account the characteristics of pawn structures on a chessboard as well. We used techniques for information retrieval from text documents, using an open-source library Apache Lucene. Partly, the development took place in the environment Jupyter Notebook, which enables simple visualization of chess positions. The search of positions with similar content can be used for automatic preparation of chess trainings, whereby the job of chess trainers can be made easier. We could improve the algorithm for searching similar positions by recognising dynamic, tactical motifs. The competence of the programme for discovering positions with similar content was confirmed by a survey carried out among chess players

Application for Management and Analysis of Data About Games of Chess

Tato bakalářská práce se zabývá návrhem a implementací systému pro správu a analýzu dat ze šachových partií. Partie jsou uchovávány v úložišti dat, do kterého jsou nahrány pomocí vytvořeného systému. Byl implementován také algoritmus AprioriAll, který je použit k nalezení sekvenčních vzorů v uložených datech. Kromě toho jsou také implementovány funkce vytvoření stromu a vyhledávání v datech. Data o šachových partiích jsou uloženy ve standardním formátu PGN.This bachelor thesis deals with design and implementation of system for management and analysis of data about games of chess. The games of chess are stored in a database, to which they are uploaded by means of the system. There is also the AprioriAll algorithm implemented to find sequential patterns occuring in the data. Except of mining sequential patterns, the functionality of tree creation and searching in the data is also implemented. The data about games of chess are stored in a form of standard PGN files.

Система для пошуку найкращого шахового дебюту за статистикою гравців різних рівнів

Мінін П.А. Система для пошуку найкращого шахового дебюту за статистикою гравців різних рівнів. КПІ ім.. Ігоря Сікорського, Київ, 2023. Проєкт містить 60 с. тексту, 11 рисунків, 15 таблиць, посилання на 28 літературних джерел та 4 графічні матеріали. Об’єктом дослідження проєкту є процес пошуку найкращих шахових дебютів. Мета розробки – надання практичного рішення проблеми побудови шахового дебютного репертуару шляхом автоматизації пошуку у відкритих базах даних партій. У дипломному проєкті розроблено фрагменти системи для пошуку найкращого шахового дебюту за статистикою гравців різних рівнів, а саме: алгоритм пошуку найкращого шахового дебюту за обраними параметрами, що використовує рекурсивний пошук вглиб, а також графічний користувацький інтерфейс. Проведено ретельний аналіз та вибір технологічного забезпечення, котре було б найбільш оптимальним для вирішення поставлених задач. Значну увагу було приділено налаштуванню комунікації між системою та сервером, що обробляє статистику, і обробці даних різних видів для побудови сучасного програмного забезпечення у сфері шахів. Отримані результати можуть бути корисними шахістам усіх рівнів та будь-яким іншим шаховим ентузіастам при побудові дебютних репертуарів чи проведенні власних досліджень.Minin P.A. System for searching the best chess opening based on players' statistics at different levels. Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, 2023. The project consists of 60 pages of text, 11 figures, 15 tables, references to 28 literary sources, and 4 graphical materials. The object of the project research is the process of searching for the best chess openings. The development goal is to provide a practical solution to the problem of building a chess opening repertoire by automating the search in open databases of games. The graduation project includes the development of fragments of a system for searching the best chess opening based on players' statistics at different levels, namely: an algorithm for searching the best chess opening based on selected parameters using recursive depth-first search and a graphical user interface. A thorough analysis and selection of technological infrastructure were carried out to find the most optimal solution for the defined tasks. Significant attention was given to configuring communication between the system and the statistics-processing server, as well as data processing of various types to build modern software in the field of chess. The obtained results can be useful for chess players of all levels and any other chess enthusiasts in building opening repertoires or conducting their own research

Decision-making and strategic thinking through analogies

When faced with a complex scenario, how does understanding arise in one’s mind? How does one integrate disparate cues into a global, meaningful whole? Consider the chess game: how do humans avoid the combinatorial explosion? How are abstract ideas represented? The purpose of this paper is to propose a new computational model of human chess intuition and intelligence. We suggest that analogies and abstract roles are crucial to solving these landmark problems. We present a proof-of-concept model, in the form of a computational architecture, which may be able to account for many crucial aspects of human intuition, such as (i) concentration of attention to relevant aspects, (ii) \ud how humans may avoid the combinatorial explosion, (iii) perception of similarity at a strategic level, and (iv) a state of meaningful anticipation over how a global scenario \ud may evolve