Chess AI: A Brief History | So Good News


Chess is a two-player strategic board game played on a chessboard of 64 squares arranged in an 8×8 grid. Played by millions of people around the world, chess is believed to be derived from the Indian game of chaturanga dating back to the 7th century.

Chess has gained immense popularity and is growing as more people start playing during the global pandemic. There is no better time to analyze the role artificial intelligence improving the quality of chess.

A Brief History of Chess AI

  • 1951: Alan Turing published the first program on paper that could theoretically play chess.
  • 1989: World chess champion Garry Kasparov defeated IBM’s Deep Thought in a chess match.
  • 1996: Kasparov defeated IBM’s Deep Blue in another match.
  • 1997: IBM’s Deep Blue became the first chess AI to beat a grandmaster in a match.
  • 2017: AlphaZero, a neural network-based digital automaton, beat Stockfish 28-0 in chess matches with 72 draws.
  • 2019: Leela Chess Zero (LCZero v0.21.1-nT40.T8.610) defeated Stockfish 19050918 53.5 to 46.5 in a 100-game match for the Top Chess Engine Championship Season 15 title.
  • Current: Modern chess AI engines use deep learning to learn from thousands of matches. They consistently have a FIDE rating, the chess rating system, of over 3400, far above the best human players.

Artificial Intelligence a revolution numerous by itself feats of achievements. It is enough to use AI in the real world and in real scenarios. It covers a wide range of use cases to improve the overall quality of life. Another great use of artificial intelligence is in chess.

We will first look at a brief introduction to the history of AI in chess. Next, we will learn about the modern evolution of chess engines and the impact of AI in the chess world. Finally, we conclude why every developer should try to implement similar chess engine programming. Without further ado, let’s get started.

History of Chess AI

In 1951, Alan Turing published the first paper-based program that could play a complete game of chess. In the years that followed, there were successive developments. During this period, new chess games and chess engines were developed. However, these AI chess engines have not been highly successful, perhaps due to the lack of efficient resources and tools.

In the 1980s, world chess champion Garry Kasparov vehemently argued that AI chess engines would never be able to beat top chess grandmasters. His statement would remain true for years to come, as he successfully defended his throne in 1996 with a 4-2 match against IBM’s Deep Blue in six games. It also defeated Deep Blue’s predecessor, IBM’s Deep Thought, in a 1989 clash.

A year after losing to the World Champion, Deep Blue returned by defeating the World Champion in a rematch. Deep Blue won Kasparov 2.5:3.5. Although there is some minor controversy regarding the authority of this win, it is mostly considered in favor of the chess engine. In one of Kasparov’s recent interviews, he agreed that he lost fair and square.

Chess engines have come a long way from the 1950s to the current generation of chess games. In order to better understand the advancements of AI in chess, let’s analyze the modern evolution of chess engines in the next section of this article.

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The modern evolution of chess is AI

Artificial intelligence algorithms designed for human play use different principles. Although it is difficult to discuss what algorithm each engine uses for its functionality and performance, we do know that several popular engines, such as Alpha Zero, use neural networks. deep learning and automation such as neural nets. Leela uses Chess Zero open source An AlphaZero implementation, it learns chess through self-paced games and advanced training.

Today, modern chess engines are so well developed that they don’t drop a single game to human players. Even the current world champion could not beat the best modern chess engine once in 100 games. The world champion has a FIDE rating of over 2800 in all formats. The competition is usually held in a classic time format. The match was against Stockfish 9.

It has a rating of 3438 (engine rating is not a FIDE rating, but the player pool for engines is much stronger than humans, so in theory the FIDE rating for Stockfish 9 would be even higher). The result of two modern collisions of chess engines is as follows Wikipedia:

  • 2017: AlphaZero, a neural network-based digital automaton, beat Stockfish 28-0 with 72 draws in 100 games.
  • 2019: Leela Chess Zero (LCZero v0.21.1-nT40.T8.610) defeated Stockfish 19050918 53.5 to 46.5 in a 100-game match for the TCEC Season 15 title.

These results, along with the growth of chess engines and neural networks and deep learning-based chess networks, are taking the chess world by storm, a great sign of the potential for bigger and bigger possibilities. Let’s take a look at the potential impact of AI in the world of chess.

Chess How AI has affected chess

Artificial intelligence has influenced chess games at a high level. Most grandmasters and super-grandmasters (above 2700 in the FIDE ranking) use state-of-the-art AI chess engines to analyze their games as well as their opponents’ games. Now there is a complete revolution in playing chess games.

Key discovery theories and other analytical concepts are thoroughly analyzed. In classic chess formats, you’ll typically see these top-level players make 10 to 15 first moves from previously analyzed games or top mover suggestions.

With the help of these engines, the quality of high-end games has also improved dramatically. Thanks to the enormous improvements in these chess engines, it is almost impossible to rate or compare a legendary player from the past decades to a modern player.

Some argue that chess engines have had a negative impact on the game because it is more about theory than actual practice and gameplay. Others argue that AI’s impact on chess has led to dramatic improvements in competition and that progress has yet to be made to challenge modern players.

Eventually, they will make these players even better with opening theory and other tricks. There is still room for human error. These mistakes can be used by players to gain advantages and create interesting games of chess attack.

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Advantages of building your own chess AI

No matter what level of programmer you are, you’ll have a great time exploring the many aspects of building your own chess engine. I believe that programmers and developers should try game development with Python and AI.

If you a beginner, then the realization of the structure of the board and pieces, while trying to study the artistic features. You will learn the features of functions and classes to implement the structure of the board, and place the pieces in their proper places. You can experiment with the two colors of the chess board and the chess pieces. In the end, you will have a beautiful graphic design that you can develop from scratch using your coding skills.

If you are an intermediate AI developer, you can start implementing the functions of the parts and their movements. Each part has its own representation and notes for a particular movement. You need to implement these positions and also calculate the capture of each of these parts. All this does not have to be perfect to develop skills and get a job program.

Finally, for advanced programmers and AI developers, you can explore a number of games and chess engines developed in recent years. You can build deep learning using the available data neural networks for the chess engine. A chess engine can learn from games played since the 1800s. Chess has a large dataset that allows developers to create quality chess engines from scratch.

Artificial intelligence is a revolutionary phenomenon and it has changed the landscape of chess. The impact of AI on chess can be argued both positively and negatively.

However, the impact, inspiration and excitement created by AI is undeniably amazing. Artificial intelligence has great potential in the field of chess. Modern developments and advances in chess engines are growing rapidly. In the modern world of chess, we can achieve much more.

I’m excited to see where these improvements go. I also hope that you all will try to implement a chessboard or a chess engine as an interesting project.


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