Category Archives: Chess Engines

Chess has been fascinating players and spectators for nearly 2,000 years. With the technological revolution of the last 100 years, computers have become an increasingly important part of our lives, and their effect on chess has been substantial.

Hardware and software developments have given programmers a powerful environment where they can merge chess and computers together.

This article is a brief guide to understanding how chess computers (chess engines) have affected the game of chess:

A chess engine is simply a software program that plays and analyzes chess. The word engine simply refers to a kind of high-powered program that does a lot of searching and processingsimilar to a search engine.

Humans have always been fascinated with machinesincluding chess-playing machines.

In 1796, a fake chess-playing machine called the Automaton was created, but it had a strong human chess player hiding inside playing the moves. In 1912, a machine was created that could actually checkmate with a king and rook vs king.

But it wasnt until 1951 that a computer program was written by Alan Turing that could actually play chess. For the next 50 years, programmers worked on making their chess engines better, and improvements in hardware allowed for stronger play. By 2005, chess engines had definitely become stronger than the best human players. In the years since, they have improved significantly, and now there are hundreds of computer programs that are stronger than human grandmasters.

Humans have gotten better at chess over time as they learn from the collective wisdom of past players. Computers have accelerated this progress, as chess engines have added new knowledge and understanding to the game.

The top players today use chess engines extensively to analyze positions and generate ideas. Unfortunately, this has also introduced cheating to chess, where any player using merely a mobile phone and a chess engine can play better than any grandmaster.

Online chess servers like Chess.com catch hundreds of cheaters each day who cannot resist the urge to win games using computer assistance. Still, fans of the game have benefitted from engines as they have helped improving players get better through analysis, and have also created a spectator sport where top chess engines battle to see which is best.

Chess engines are complex. However, in simplest terms, they do two important things:

1. Evaluate. Chess engines look at individual positions and evaluate which position is better. Almost all chess engines display a evaluation number, or eval, based on the same scoring that most chess players use (a pawn being worth one point, a minor piece three, etc). Each chess engine does this differently, but most engines look at things like material on each side, all the threats on the board, the king safety, and pawn structure.

The cumulative score of the best evaluation in the future is summed up to one number. Traditional engines evaluate similarly to humans because they were designed by humans. Neural net engines (see below) evaluate differently.

The position below is given a cumulative score of +3 by the computer engine Stockfish even though material is equal, because White's piece development is much better. This means that the white position is roughly three pawns better.

2. Search. Like good chess players, engines try to look deeply into the position. The further ahead they can see, the better the move they can make now, as they can evaluate positions that will result after the best possible moves in the future. Each individual chess move is called a ply (a layer), and the depth is explained in how many ply deep. At 20 ply (10 white moves, and 10 black moves), most engines are already evaluating far deeper and stronger than humans. Depending on the time allowed and the complexity of the position, engines can look more than 50 ply deep.

From the current position, an engine starts to look at all of the possible moves and replies. And then all of the possible replies to that. And then all of the possible replies to that! Imagine there are 32 possible moves in any position. After four moves, there are already more than one million positions to evaluate. After just four more moves, that would be more than one trillion position. That becomes extremely unpractical.

So instead, engines try to use smart pruning to look deeply at just the most promising lines, and ignore the obviously bad ones. The engine keeps a running principal variation (PV) of the most promising moves in every position.

Traditional chess engines use complex evaluation functions and intelligent search algorithms to find the best possible move. Their power is also related to how much CPU processing power the phone, computer, or server has. The more powerful and plentiful the CPUs, the stronger the engine becomes.

A neural network (NN) engine is a different kind of chess engine. The first NN was AlphaZero, created by DeepMind (a Google company). In 2017, AlphaZero reportedly crushed Stockfish, the best traditional engine, in a 100-game match. But the match was private and many have questioned the results. However, in 2019, the open-source Lc0 (Leela Chess Zero), did finally become the worlds strongest chess engine in the Chess.com Computer Chess Championship.

A neural network is a series of algorithms and instructions used to evaluate a chess positionexcept we dont know exactly how! A NN is trained by feeding it data (in this case, chess games), and then letting it learn on its own. This is traditionally called machine learning.

The games can come from external sources (like grandmaster games). Or, as in Lc0, the game data comes from playing more than 200 million games against itself. So for NN engines, their evaluation is provided by the neural net.

The introduction of NN engines has also change how search is done. Traditional engines have typically used what is called an alpha-beta (AB) minimax search, where only the best possible moves are evaluated. NN engines, however, choose to use what is called Monte Carlo tree search (MCTS), where the best move is selected based on the probable outcomes of many playouts. Basically, it plays a ton of quick games against itself at super fast speeds with random moves and looks at the moves that seem to have the highest odds of winning.

NN engines also get stronger based on the type of hardware they are run on. They need powerful CPUs. But, even more so, they need powerful GPUs (graphics processing units, like in many gaming computers), because GPUs are faster at processing neural nets.

There are several online chess engine tournaments that match up the best engines. Chess.com runs the Computer Chess Championship, which is an ongoing series of engine-vs-engine tournaments with different engines and formats that you can watch 24/7!

There are many ways to determine the top chess engines. A lot depends on hardware, time control and methodology used. You can look at the rankings for past chess events (such as the CCC), or different online rating systems. Themost recent CCC was won by Lc0, with Stockfish second, Leelenstein third and Antifish fourth.

Traditional Chess Engines:

Neural Network Engines:

Stockfish is an open-source chess engine developed by a large community of chess engine enthusiasts and developers. It has been the strongest traditional chess engine since 2016. Many of the modern chess engine programming methods were pioneered through Stockfish. It uses a complex eval formula and A/B search.

Komodo is a private commercial engine originally developed by Don Dailey and now continued by Mark Lefler and grandmaster Larry Kaufman. How it works is not publicly known, but it claims to rely on a more sophisticated evaluation based on grandmaster understanding and the insights of GM Larry Kaufmann, which is supposed to give it a more human style. It uses a traditional A/B search. It is currently the second strongest traditional chess engine.

Komodo MC is the Monte Carlo search version of Komodo. While the evaluation is the same as regular Komodo, the way it searches is with Monte Carlo tree search instead of A/B minimax. While not quite as strong as regular Komodo, it is improving more quickly.

Houdini is a private commercial chess engine published by Robert Houdart. It has a very fast search and performs well in faster time controls. It loses very few games, and can escape from difficult positions (like its namesake). It is currently the third-strongest traditional chess engine.

Fire is a private non-commercial chess engine by Norman Schmidt. It was originally released in 2010.

Ethereal is a relatively new open-source chess engine by Andrew Grant, developed mostly as a way to learn and improve his programming. It was created in 2016, and was inspired by Stockfish and other chess engines.

Shredder (or Deep Shredder) won many tournaments and titles in the 1990s and went commercial in 1996. Stefan Meyer-Kahlen is the author.

Laser is an open-source chess engine created in 2015 by the brothers Jeffrey and Michael An, technology students in California.

Lc0 (Leela Chess Zero) is an open-source, community-driven neural network engine. Lc0 has a net based on reinforcement learning, which means it has played itself more than 200 million games, and learns only from playing itself. When it first starts its training, Lc0 knows nothing more than the rules of chess.

It uses a Monte Carlo tree search to choose its moves. Lc0 is currently the strongest chess engine in the world, winning the Chess.com Computer Chess Championship in 2019. Lc0 plays a very different kind of chess from Stockfish. It creates exciting, attacking play, and makes moves that traditional chess engines do not understand. Lc0 tends to play endgames in a strange way, often giving up material on purpose to simplify the game instead of choosing the quickest win.

Leelenstien uses most of the code of Lc0, but has a different neural net based on supervised learning, being fed millions of previously-played chess games from chess engines, as opposed to learning from its own games. This net has proved to not be quite as strong as Lc0s net.

Antifish also uses most of Lc0s code, but has a neural net based solely on games played between Lc0 and Stockfish, in an effort to beat Stockfish. Antifish is not as strong as Lc0 or Leelenstein.

Allie is a unique NN engine written by Adam Treat. Allie uses its own Monte Carlo search, move selection, and time management code. Allie can be used with any net, and does not have a net of its own. The Allie author is looking to add A/B search to his engine.

Do you have any questions about computer chess engines? Let us know in the comments.

If you want to watch some of the world's top computer engines play right now, tune in to the Chess.com Computer Chess Championship here.

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Computer Chess Engines: A Quick Guide - Chess.com

Over the past 10 years, there have been a handful of truly dominant chess enginesKomodo and Stockfish have been battling at the top of the chess engine world since 2013. Let's learn more about the insanely powerful chess engine Komodo.

Here is what you need to know:

Komodo is one of the strongest and most successful Universal Chess Interface (UCI) chess engines on the market. It was originally developed by Don Dailey in 2010 and was further developed by Mark Lefler in 2013. GM Larry Kaufman has been supporting and improving the engine for many years as well.

Komodo was acquired by Chess.com in 2018 alongside the release of Komodo's "Monte Carlo" version. Unlike most conventional chess engines, Komodo Monte Carlo selects its moves by win probability and not with the traditional alpha-beta pruning method. This methodology is similar to the machine-learning chess projects AlphaZero and LeelaChessZero.

Komodo gains an edge over conventional brute force engines because of its positional style of play and the fact that it relies on position evaluation over depthwhen most engines can't find a good plan, Komodo can seemingly create something out of nothing. These are just two of the factors that contribute to Komodo's long-term success and an impressive number of world championships.

Komodo has the ability to run at different playing strengths and with different styles and opening books, which is a very popular feature for chess players. It runs on many platforms including Windows, Mac OS X, Linux, and Android. Although it is a commercial chess engine, earlier versions are free.

Komodo has won many top-level engine championships: CCT15, three Top Chess Engine Championships (TCEC), multiple World Computer Chess Championships, multiple World Computer Blitz championships, and multiple World Chess Software championships. According to the October 2020 computer chess rating list (CCRL), Komodo is ranked third in the world with a rating of 3419.

Stepping onto the scene in 2010, Komodo had its first major success in the CCT15 tournament in 2013 when it placed first with a score of 6.5/7 ahead of Hannibal, Crafty, and 21 other powerful engines.At the end of 2013, Komodo defeated Stockfish in the TCEC season 5 superfinal. In TCEC season 6 it reached the superfinal against Stockfish again (but lost this time). In 2014 and 2015 Komodo again faced Stockfish in the TCEC superfinals for seasons 7 and 8; Komodo won both of these championships.

In 2016 Komodo won the World Computer Chess Championship and the World Computer Software Championship. In 2017 it again won the World Computer Chess Championship and also won the World Computer Blitz title.Komodo repeated as World Computer Blitz champion in 2018 and again won the World Computer Chess Championship and the World Chess Software Championship in 2019.

It is easy to play against Komodo on Chess.com! As mentioned, Komodo can play at different strengths and playstyles. Chess.com has recently released over 60 computer personalities and a new interface to play versus the computer! All you have to do is go to Chess.com/play/computer or hover over the "Play" option in the menu bar and select "Computer":

After you select "Computer," you can choose the computer personality you want to play against! They can even converse with you in certain situations.

Another method of playing Komodo on Chess.com is to go to Live Chess and select the "vs Computer" option below the "Play" button.

After selecting the "Play" button, you are given many different personalities and playing strength options that range from around 700 all the way up to the Hikaru-bot and KomodoBoss!

After you select the bot you'd like to play, you select your preferred time control, whether you want the game rated or unrated, and your preferred color. Next, select the "Play" button.

Your game against Komodo then starts automatically.

You now know what Komodo is, what it has accomplished, how to play against it on Chess.com, and more. Head over to Chess.com/CCC to watch Komodo and other top engines play at any time on any day!

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Komodo - Chess Engines - Chess.com

Anish Giri was two pawns up in and endgame with rooks and minor pieces in his crucial encounter against Alireza Firouzja in round 12. Eventually, that turned into a position with four passed pawns against a knight, with a rook per side on the board. For a long time it seemed like Giri was heading to a victory, in which case a draw in the final round would have been enough to secure tournament victory. However, Firouzja never stopped creating practical problems for his opponent and was rewarded with a half point after a lengthy struggle.

Understanding Middlegame Strategies Vol.1 and 2

These DVDs are about Understanding Middlegame Strategies. In the first DVD dynamic decisions involving pawns are discussed. The second DVD deals with decision making process concerning practical play.

The 17-year-old wunderkind commented:

It was a miracle. I guess it was payback for yesterday the same thing happened yesterday, so Im very happy for the result and I look forward for tomorrow.

Firouzja referred to the chances he missed against Fabiano Caruana in round 11, when he was first in deep trouble and then got a clearly better position after the time control. No matter what happens on Sunday, Firouzja has once again proved he is not only amazingly strong but also a fearless fighter. And he could still end up winning the tournament!

In fact, there are five players who still have theoretical chances of taking the title. Giri, of course, who will play black against David Anton; Firouzja (white against Wojtaszek), Caruana (black against Tari) and Jorden van Foreest (white against Grandelius) are a half point behind; while Andrey Esipenko (black against Donchenko) would need a number of results going his way to catch up with Giri, as he is currently trailing the leader by a full point.

The action on Sunday starts two hours earlier, at11.00 UTC (12.00 CET, 06.00 ET).

Another lengthy and enjoyable edition of the tournament is coming to an end| Photo: Jurriaan Hoefsmit

It does not make sense to keep calling Firouzja a talented rising star, as he has so far gained 10.8 rating points in Wijk to reach the 14th place in the live ratings list he isprovisionally aboveVishy Anand, Hikaru Nakamura and Peter Svidler in the ranking. And on Saturday he demonstrated that he is not all about tactical skirmishes and spectacular attacking wins, as he defended a worse position for hoursagainst one of the strongest technical players in the world.

Against 1.e4, the youngster played the French instead of his usual Caro-Kann Defence. Giri, also a renowned theoretician, was ready for the challenge, and played a line which Firouzja described as a very good, solid way to get a better endgame.

Firouzja considered his 36th move to be a key mistake:

The Classical French - Main Line

After 1.e4 e6 2.d4 d5 3. Nc3 Nf6 4. e5 Nfd7 5. f4 c5 6. Nf3 Nc6 7. Be3, the author takes a detailed look at a daring line with 7... cxd4 8. Nd4 Qb6, as well as the quieter plans with 7...cxd4 8. Nd4 Bc5, and the main line with 7... a6 and b5.

Instead of 36...Kf8, the youngster thought 36...f6 was better in order to bring his king to the centre more quickly.

Nine moves later, White had two passed pawns on the queenside, and it seemed a matter of time before he converts his position into a win:

Converting this into a full point is by no means trivial, especially five hours into the game in the twelfth round of a tough elite tournament. However, as Giri pointed out, playing 47.a4 only complicated matters for white, as he will always need to keep an eye on his b4-pawn.

Soon after, Giri agreed to give up his bishop to get four passed pawns (connected in pairs) against Blacks knight, with the rooks still on the board:

This position is still winning for white, but Firouzja continued to findthe most stubborn defensive resources until a draw was agreed on move 67.

Nigel Short explained on Twitter:

German GM Karsten Mller took a closer look at the complex ending seen in the most important game of the round.

Still the favourite to win the event Anish Giri| Photo: Jurriaan Hoefsmit

After his loss against Van Foreest on Friday, Pentala Harikrishna immediately bounced back to a fifty-percent score by beating Alexander Donchenko with the white pieces. The players reached a sharp heavy-piece endgame which the engines evaluated as equal. But, with queens still on the board, a single slip can lead to disaster:

Chess Endgames 3 - major piece endgames

The third part of the endgame series tackles queen endings, rook against minor pieces, queen against rook and queen against two rooks. Queen endings are not nearly as mysterious as they appear at first sight. Knowing a few rules of thumb and principles will make things very much easier for you.Over 7 hours video training.

42...Qxc3 was playable here for black, while his 42...Qf6 turned out to be the deciding mistake. Harikrishna spent two minutes deciding on 43.c5, when White gets to coordinate an attack first. There followed 43...dxc5 44.Rxc5 a3 45.e5 Qh8 46.Qb4:

White threatens a deadly discovered check and there is no defence for his opponent. After 46...Qa8+ 47.Kh2 Ke8 48.Rb5 Qc6 49.Rb8+ Kd7, a double attack put an end to the game:

50.Qd4+ and Donchenko resigned.

Endgame specialist Karsten Mller analysed how Black could have defended from the critical position that arose on move 42, noting that constellations with queens and rooks have endgame and middlegame components.

Alexander Doncheko was invited as a late replacement| Photo: Jurriaan Hoefsmit

Out of a Petroff Defence, Maxime Vachier-Lagrave and Jan-Krzysztof Duda both currently on 5/12 in the standings table reached the following endgame by move 29:

Magical Chess Endgames

In over 4 hours in front of the camera, Karsten Mller presents to you sensations from the world of endgames - partly reaching far beyond standard techniques and rules of thumb - and rounds off with some cases of with own examples.

White played the imprecise 30.d5+ here, and further worsened his position in the next move. Duda, however, was not able to finish off his opponent and a draw was agreed after 76 moves.

GM Mller took a closer look at the instructive ending with rooks and minor pieces.

Jan-Krzysztof Duda checking his colleagues game;while Giri calculates his difficult ending against Firouzja?| Photo: Jurriaan Hoefsmit

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Tata Steel R12: Almost there - Chessbase News

Dec 28, 2020 (UNI\\\\TNM): Technology has advanced so much over the last two decades in particular, that the way we play games has changed completely.

Artificial intelligence has allowed for more bespoke experiences, while virtual reality has created games that are more immersive than it was ever believed to be possible.

The greatest impact in the industry was made by software development.A countless number of games are now available on a single device, which can be carried around everywhere, which has led to a trend of technology meeting tradition. We explore this by looking at a few traditional Indian games that have been upgraded to the 21st century.

Source: Pexels

Board games have been popular in India since ancient times and the industry is now larger than most people realize. By 2023, the market is projected to grow by 17%, which would amount to several billion dollars. Traditional board games such as Pachisi or Chaupar are available in more formats than just physical versions as developers combine various technological advancements to enhance the player experience.

The most obvious way in which tech has been integrated into board games is with mobile apps. Smartphone and tablet users can go on a virtual app marketplace and download the game they want. A guide would then teach users how to play. Features such as sound effects, time trackers, or the possibility to add multiple players, creates a more immersive experience and increases the games accessibility. On top of that, there is no need to carry around heavy boxes and worry about losing any pieces.

Playing cards are among the most common forms of entertainment in India, and it has existed in the country since the 16th century. Back then, the royal Indian courts used decks of cards made from precious materials to play. Now, most households have a deck of cards and know how to play a few games, with one of the most popular games being andar bahar.

This is a traditional Indian game that people used to play this game in the streets, historically. In present day, people can play andar bahar online with a choice of online casino, as well as read about the history of the game, thanks to the technological advancements that we now tend to take for granted. Increasingly sophisticated software has even made it possible to play this game live online, in front of and with a real-life dealer, using only a computer or a smartphone.

Source: Pexels

Invented in India around the 8th century, chess has changed numerous times throughout the years. However, it was only in the 20th century that the game itself was significantly revolutionized by the invention of databases and chess engines which have made online chess games the new norm. Chess engines can be run on any computer and are so powerful that they can show people the best moves in each position, while also evaluating each move. This has also changed the way people learn how to play the game.

Board games and cards bring people together and they are as popular now as they were decades, or even centuries ago, just in a different format. Technology is making them more accessible and is creating a new digital generation of gaming which is proving to be a resounding success with a bright future.

(Disclaimer--Features may vary depending on the regions; subject to change without notice.)

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How Tech Has Changed Traditional Indian Games - United News of India

2020 has been a unique year for chess. In the first half, as countries across the world went into lockdowns to stem the spread of covid-19, millions discovered the gameonline. Websites like chess.com, chess24.com and lichess.org saw a sharp jump in the number of users and games played. In the second half, Netflix released The Queens Gambit, a web-series about a female chess player battling her demons to beat the best in world chess. The games popularity surged. Unfortunately, so did cases of cheating.

In a post in August, chess.com, the biggest of the online chess platforms, said closure rates of accounts had more than doubled since the covid-19 outbreak in December 2019. The website had been closing nearly 500 chess accounts every day. Offences included using chess engines to play matches, rating manipulation, sandbagging (deliberately losing games to lower ones rating and become eligible for lower-rated tournaments with prize money) and other fair-play violations. Those against whom action was taken include grandmasters, the elite players in world chess.

The director general of the world chess body FIDE, Emil Sutovsky, has been quoted as saying that stemming cheating is a huge topic I work on dozens of hours each week. Its president, Arkady Dvorkovich, has called computer doping a real plague. In chess.com's history, from 2007 till August 2020, we have closed nearly half a million accounts for cheating, the website says. Our projections predict we will reach 500,000 accounts closed by February 2021 and one million accounts by mid-2023. There has been a sharp jump since the outbreak. In December 2019, it had shut 6,044 accounts. In August, it closed 15,130.

So how does one stop cheating in online chess?

A photo taken in Melbourne on November 25, 2020 shows the web page of Chess.com showing more than 46 million members with 7.5 million matches played today and over 158,000 people online. (Photo by William WEST / AFP) (AFP)

This was the question Sotirios Logothetis and his team at chess24.com found themselves faced with when they decided to organise online tournaments earlier this year.

Cheating is extremely rare in offline events, especially at the top tier, says Logothetis, who is also an international chess arbiter. The main advantage there is, you have full visual contact, which allows the arbiter to latch on to suspicious behaviour. In addition, marquee tournaments also use metal detectors and check the players physically for sophisticated devices, like a micro earpiece with voice transmitters. Online chess doesnt offer these advantages, says Logothetis.

The solution, Logothetis team found, lay in the way some universities around the world conduct examinations: webcams and screen-share. In the tournaments they have conducted since March, including the rapid-chess tournament Skilling Open and the Magnus Carlsen Invitational, each player had to have at least two cameras: one in front, another at the back or the side. They also installed a software so that the computer screen could be shared with the arbiters during playing sessions.

The cameras, which the organisers sent to the players houses, stored the audio and video footage in a memory card even if the internet connection was interrupted. After each session, players were expected to upload the entire footage on the server cloud. These two tournaments had around a dozen players each, so it was possible to send equipment, upload and verify.

Most online tournaments conducted this year, including the FIDE Online Olympiad 2020, have used a combination of such techniques. There is even a system to scan a players game, study performance patterns and highlight unusual activities, such as if a player is making the kind of moves a chess engine would, or if a low-ranked player suddenly starts playing exceedingly well. Anything, in other words, that doesnt fit the pattern.

I think our systems can cover 95% of possible ways of cheating online, says Logothetis. But, he accepts, it can never be foolproof. If someone tries really hard to cheat, I think they will find a way, he adds. But someone who is doing this has to be truly dedicated.

So, while marquee tournaments may have developed robust systems, for most online players cheating is only a few clicks or fingertaps away. The simplest way is, you have a phone, enter a question and ask for the best moves, says grandmaster (GM) Srinath Narayanan. Stockfish (the best open-source chess engine) is free and easily accessible. There are also extensions on web browsers that show the next best move.

Its possible to game a platforms in-built scanners too. If someone is smart, they can make a couple of moves by themselves, and for some important ones, they can take the help of engines, says GM Harika Dronavalli, Indias No.2 woman chess player.

Cheating is rampant in online chess, Narayanan reckons. Its not just a matter of pridesome tournaments offer cash prizes too. Narayanan, who coaches the 16-year-old chess prodigy Nihal Sarin, says: I know young kids also have cheated during games. Some of them have been caught and banned by popular websites, some havent been. The penalties arent strict enough, he adds. If you confess, you dont play in prized events for a year but you can have your account back. And if a player is banned from one website, they can always play on another.

Two men play Chinese Chess along a street in Beijing on October 28, 2020. (Photo by NICOLAS ASFOURI / AFP) (AFP)

Some platforms, however, are keen on setting an example. In October, chess.com suspended Armenian GM Tigran Petrosian for allegedly using computer assistance during the finals of the Pro Chess Leagueone of 46 GMs against whom action has been taken since 2007. In its investigation, the website found that some of Petrosians moves were consistent with chess-engine suggestions. He also allegedly looked down often, which the investigators concluded was to consult a computer. Petrosian has vehemently denied the allegations.

I was surprised when I saw Tigrons news, says Dronavalli. Most players I know wont think of that. Even if there are people who are ready to cheat, I dont think they should take risk of a whole career for an online tournament.

In the past year, Dronavalli has played several marquee online tournaments, including Titled Tuesdays, Online Chess Olympiad and the Online Nations Cup. For the most part, she says, the checks were robust: You shared your screen during gameplay, you couldnt mute yourself and you couldnt open any other files on the computer. Before a game, the organisers would ask for a camera-tour of the room she was playing in. If I switched off my webcam or exited the room, I would have to repeat the whole thing all over again. It would get tiring sometimes but you have to do it.

She, too, acknowledges that anti-cheating measures can never be as foolproof as they are for an offline event. But cheating will only get you so far. Finally, you need to have talent, says Dronavalli. If you are not consistent, no one will believe your performances.

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2020: The year of a pandemic of cheating in online chess - Livemint

Its no secret that artificial intelligence (AI) programs are good at mastering games. From chess to Go to StarCraft II, humans are often no match for the computer. One thing that previous AI game engines have in common is that they were taught the rules of each game before learning to play it.

Now, researchers from DeepMind have taken things a step further, Engadget reports. The Alphabet subsidiary just announced that its MuZero AI is capable of playing a variety of games (and crushing human players) without being told the rules. Thats an incredibly impressive achievement and demonstrates how far the field of AI has come in the past few years.

When DeepMind unveiled its original AlphaGo AI in 2016, the world took notice. The crafty algorithm was capable of beating the worlds best human players in the ancient strategy game, Go.

It then topped the original version by creating AlphaGo Zero, an AI capable of learning to play Go simply by playing against itself. That was a step up from the original version, which learned by watching people play.

From there, DeepMind branched out. It taught its AlphaZero algorithm to play Go, chess, and shogi. Being able to master all three games was another impressive accomplishment.

The companys latest algorithm, MuZero, is a sort of combination of every iteration. Not only did it forgo the need to hear the rules of the three games noted above, it also knows how to play a suite of classic Atari titles. The algorithm learned to play all of the games on its own and is even better at them than any other version that DeepMind has created so far.

This addresses a problem that researchers have been pondering for some time, notes Engadgets Igor Bonifacic.

Its difficult to train an AI to strategize and plan ahead when it doesnt know the rules of the game thats being played. In the real world, there is no such thing as a simple set of rules. Thats what makes this breakthrough so important for the world of AI.

DeepMinds MuZero combines aspects of two prediction models that researchers have used in the past to try and solve the problem of predicting something that isnt governed by a strict set of rules.

This means that MuZero is thinking a lot more like a human than a computer. It must rule out factors that arent likely to impact the overall outcome to focus on the ones that will.

DeepMind likens this to looking at a sky full of storm clouds. In a blog post, the company says, For example, if we see dark clouds forming, we might predict it will rain and decide to take an umbrella with us before we venture out. Humans learn this ability quickly and can generalize to new scenarios, a trait we would also like our algorithms to have.

MuZero represents a big leap forward in AI technology. DeepMind notes that it has potential applications in fields like robotics, industrial systems, and other messy real-world environments.

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DeepMind's MuZero AI masters games without knowing the rules - The Burn-In

Artificial intelligence (AI), which is the simulation of human intelligence, has become very prominent in the news, discussions and applications over the past five years. But the truth is that AI has been around for much longer, as I started developing AI applications back in 1987.

Today, we are surrounded in our daily lives with AI in social media, online shopping, Google search engines, ridesharing, commercial flights (autopilots), banking and many more. Since it is difficult for most us to identify these implementations, and since we cant distinguish between AI and non-AI systems, there are four basic forms of AI and I will explain them as follows:

1. Reactive machines good examples are IBMs Deep Blue, which beat the international chess grandmaster Garry Kasparov in the late 1990s.

2. Limited memory machines that look into the past, such as parts of self-driving car software.

3. Theory of mind these machines are more advanced and not only form representations of the world, but also entities in the world. It is this replication of how humans and creatures in the world have thoughts and emotions which affect their own behaviour.

4. Self awareness this is the most advanced form of AI where these machines/systems develop a consciousness. Conscious beings are aware of themselves, know about their internal states and are able to predict feelings of others. The movies iRobot and Terminator are very good examples of this self awareness.

Why is there such excitement surrounding the first few levels of implementation of AI today? It is because we can use these AI systems/algorithms to handle massive amounts of data and learning, then developing patterns in this data, which we humans cant do as efficiently. They operate without breaks, and they continue to learn at a speed of the computers that they operate on, 24/7. Good examples can be found in the medical field. In radiology, AI has achieved the ability to detect cancer in mammograms at a 96.6 per cent specificity level, which is much greater than the average radiologist today. It continues to learn at breakneck speeds, continually getting better with its discovery of cancer.

Now, how do we translate these systems and examples to our world of yachting?

The examples that I am about to give may frighten, or even anger, some people who might feel that their own professions are at risk. But in reality I believe that this assistance will allow us to be freed up to perform tasks that we are much better at.

Navigation

This is an easy one as we move into self-learning autopilots, that are connected online with volumes of information about sea conditions, weather patterns, direct reporting from other ships and yachts, along with on-board navigation instrumentation. They can make much better decisions and never become distracted. This is happening today, in the shipping industry, in a limited fashion.

Cybersecurity

The only way to combat dynamically changing data attacks is to deploy sound and sophisticated AI appliances that morph their shields incautiously to protect the integrity of the yachts systems, and the owners data.

Security

We are using AI routines in our security systems to understand the patterns of the yachts operation, identifying intrusions more quickly and immediately identifying the correct access to all areas of the yacht through facial recognition.

Alarm, monitoring and control (AMS) Another area that benefits from the use of AI algorithms. These algorithms move the AMS from a reactionary system to a truly forward-watching and preventive system.

Owner/guest services

By implementing AI to learn the patterns of the owner and guests, these systems can then anticipate their needs. Simply knowing their system vitals such as blood pressure, heart rate, temperature would allow an AI-driven guest services system to react precisely and immediately. I envision that robotics will be deployed in the future to interact directly with the owner and guests. Consistency in this service would be a major benefit, along with the ability to be available at all hours of the day and night to the varying schedules of each individual.

Entertainment systems

These systems, in general, have the label of AV (audio visual). I have a design for a living yacht, where the yacht reacts dynamically to the individual and/or individuals in an area of the yacht. Using AI learning we can change the environment in the area of the yacht to provide the entertainment experience that is matched directly to the audience, including their current temperament and past histories of likes, which will provide the ultimate user experience.

Approaching AI with the right attitude is very important, and it might be best to consider it as a tool with which to make our lives better and easier. As individuals, we will not stop the implementation of AI in our daily lives. If we embrace it, we can help steer the direction that it is headed so that it benefits us.

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While playing chess online has been around for a few decades, during the pandemic homebound players have grown the game exponentially. CBS News quoted Grandmaster Maurice Ashley as saying the pandemic has driven people indoors, and theyre looking for something incredible, constructive, educational to do.

Moreover, the Netflix hit series The Queens Gambit has sparked increases in searches for learning chess. For the most part, the mainstream media portrays chess as a worthy, honest game. A CNN article stated, Chess is a game of intellect. Remember intellect? In a world where every news development seems more implausible than the last, there is something infinitely reassuring in retreating to a series about a cerebral game, in which (this is not spoiling anything, I think) nobody cheats.

Notwithstanding that CNN articles positive interpretation of The Queens Gambit, there is a long history of over-the-board cheating in chess and more recent incidents of online chess cheating. And there have been some mainstream news articles recently, such as this one from The Guardian, about a recent rise in online chess cheating.

Increased cheating could derail the chess publicity train. Rather than being seen as a game that encourages intellect and truth, chess might be dismissed as a game for cheaters. Chess websites have stepped up their anti-cheating efforts, though perhaps with some unintended consequences.

Cheating accusations may harm streamers who are trying to grow the game. During ChessCoachJohns Twitch stream on November 17, someone in his Twitch chat suggested a move, on the fifth move in a standard opening. The suggestion was made despite John Hendrick, aka ChessCoachJohn, having a warning against suggesting moves in his chat rules and Hendrick regularly reminding his viewers not to offer suggestions. Nevertheless, the lichess4545.com moderators forfeited Hendrick in that game. Hendrick said, As a result of almost being banned from the lichess4545.com league, I implemented prohibiting all the 64 squares in my chat. For example, if someone tries to type a4 it wont appear in my chat. In addition, I added a banner below my chess board as a reminder to not suggest moves. Despite making these changes, I still feel vulnerable to future cheating accusations. When streamers such as Hendrick share their thought processes aloud, to help their viewers improve at chess and to entertain, they may make themselves vulnerable to cheating accusations.

Chess cheating accusations against children may be even more troubling than accusations against adults. No parent wants to get an email from a chess website accusing their child of cheating.

In the 1993 film Searching for Bobby Fischer, at an in-person scholastic tournament, the parents accuse each other of cheating and then physically fight. The tournament directors lock the parents in a different area, away from the playing hall. The children cheer and continue their tournament games, playing honestly.

At national tournaments for kindergarten and first grade students, parents are not allowed in the playing hall. For older childrens games, parents may be in designated areas but not in the aisles between the boards. See the US Chess National Scholastic Chess Tournament Regulations. In contrast to these over-the-board regulations, perhaps parents should be with their children, and especially their very young children, during online chess tournaments.

According to National Master Jeff Ashton, owner of Panda Chess Academy, having parents nearby may be necessary for very young children, who cannot navigate technical glitches on their own. Recently, a six-year-old student of Ashtons, left alone during a tournament, missed a round because he kept waiting for the game to start. He was scared to touch the screen because he wanted to follow all instructions to the letter. But he should have refreshed his browser to make the game begin. Parents can help by refreshing screens, reminding children to close all open tabs and avoid switching windows, turning off phones, contacting help desks, etc.

On the other hand, some chess parents can barely contain themselves during their childrens games, wanting to kibitz their suggested moves to their offspring. Just like the children in the Searching for Bobby Fischer playing hall, children competing online from home may hate for their parents to be in the room.

Yet, as children grow older, and improve at chess, they have more incentives and means to cheat. For example, an older child understands Stockfishs decimal point evaluations. They may be tempted to use their knowledge to help them win. Winning feels good, and gaining rating points means admiration from parents and peers. Older children may also socialize in ways that leave them vulnerable to online predators, such as chatting, joining teams and groups, or using their real names.

Online chess seems like a perfect babysitter, but its not so simple. Fair play and child safety may be compromised. Here are some steps to take before, during, and after childrens online chess games.

According to Ashton, coaches should regularly discuss integrity and sportsmanship with children. Cheaters never win, winners never cheat, and other sayings about honesty might come off as corny but should be repeated to children before chess games.

Coaches and parents should also advise children to avoid multi-tasking. Phrase that advice in a positive way, that having a singular focus on a chess game is a great way to improve at chess. What it takes to be a good chess player, such as entering flow (deep concentration), also avoids cheating.

Mating Patterns

On this DVD, Grandmaster and worldrenowned commentator Maurice Ashley reviews some of the most interesting patterns with examples meant to educate and entertain.

If parents are not in the room with their children, technology can help. Ashton said, I saw one parent use an old baby monitor to keep tabs on a first grader, who, to my surprise, seemed happy to play on camera. Parents must supervise, so they can say with certainty, I am 100% sure that my kid never cheated. If parents dont want to use cameras, then they should check on their children regularly. They could also install software that manages how children use their computer time.

Parents should understand that online sites rules are strict, and that their childrens reputations are at stake. The following checklist is for parents or coaches to share with children:

1) Have no phones or devices other than the one used to play chess. 2) Do not disturb mode on! No siblings or friends should be able to message you or talk to you while playing. This is your time.If they tell you a good move, you have received unsolicited advice. 3) Make sure you have no notes, books, or any tools on your desk. 4) Close other apps. Stay with one tab. It should be you and the chess board. 5) If you are playing in an online tournament, the only modification to this advice is to have a backup computer, and possibly a backup Internet solution. Or just play the odds, and be willing to lose a game because of technical problems.

If your child is accused of cheating or actually cheats, there are several steps to take. According to Ashton, who earned an undergraduate degree in psychology from The University of Texas at Dallas, very young children sometimes dont know what is right or wrong. However, Ashton believes that most scholastic chess players understand what is fair and not fair. Ashton advises parents to ask your child what happened.

Remember that many children have cheated at chess. Parents may feel that they and their children should not admit guilt, as if chess cheating is a legal mistake. In chess, however, its best to say sorry, and move on.

Before your child loses access to a chess website, due to being banned for cheating, download all of his or her games. The parents should do this on their own, to avoid conveying to their child that they support cheating. At the same time, chess games are very valuable. If the child is going to continue at chess, then he or she should not have his chess games erased.

After downloading, close or delete the childs account. Create a new account when you, as a parent, feel that your child has learned a lesson.

Jeff Ashton teaches at his ownPanda Chess Academy

It is very rare for websites to falsely accuse a child of cheating. Ashton has only seen one case, out of dozens that he has personal knowledge of, where a cheating conviction against a child was reversed by a website. However, if you believe the cheating accusation is in error, send a polite email asking for another review. Some websites have a formal appeal process.

Its best to have an open and honest conversation with the chess servers administrators. Mention your childs age, and how you really want to learn from whats going on so that your child can also learn something.

Expect the website NOT to overturn its decision. Encourage your child to avoid misunderstandings in the future, by focusing on chess, just as they would when playing in an over-the-board tournament.

Many tournament chess players are children. Research outside of chess shows that children cheat. For example, a study of children, ages 8-12, found that 58% of participants (55 out of 95) cheated at least once during the guessing game. That guessing game was predicting what side a coin would appear on a computer screen, with 10 points awarded for a correct guess and 10 points taken away for a wrong guess. As the game started, the children were encouraged to try their best to obtain the highest score possible so they could compare their scores with their classmates. The researchers found that children with better inhibitory control and working memory will choose to cheat less often. However, once they decided to cheat, children with better cognitive flexibility will use a greater variety of tactics to cheat.

An analogy to childrens cheating during chess tournament games is possible. Children are often encouraged to do their best, to compare favorably with their chess peers. In chess, wins gain rating points and losses take away rating points. Children cheat in multiple ways, such as consulting via chat, using engines open in other windows or on phones, etc. Older children may cheat infrequently, such as only during key moments of a game, following an optimal strategy to gain rating points.

The PlayChess server

Parents may inadvertently encourage cheating, by emphasizing wins over fair play. However, research shows that most children cheat. Parents must both try to prevent cheating by children and deal with the fallout when cheating happens.

Streamers are poor role models for how to play tournament chess online, since they chat during games rather than modelling concentration and silence. Streamers educate and entertain, which is not what children should do as they play online tournament games. Remind children to concentrate fully during online tournaments as they would over-the-board: no chatting, no engines, just silent individual contemplation of the best moves to play. Just chess.

Fundamentals of Chess Tactics

Whats the easiest way to win a chess game? We all know finding a good tactic in a game can let you win a point immediately. Therefore, Fundamentals of Tactics is an excellent choice for you if you wish to learn how to start finding tactics in your games!

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Adults, children, cheating, and online chess - Chessbase News

Ian Nepomniachtchi and Sergey Karjakin have often been tied on points induring this tournament, including before todays final round. After losing to Daniil Dubov, Nepomniachtchi quickly recovered, playing for a win against Andrey Esipenko. Nepo sacrificed a pieceand then sawhis young opponent, with an extra piece, not wanting to settle for a draw when that would have been the correct decision.

Ian Nepomniachtchi vs. Andrey Esipenko

The position arose from a Petroff Defence. White tries to get something going!

16.Bxh6 gxh6 [Black takes up the gauntlet. 16...Bxh2+ 17.Kh1 Be5=]

17.Qg4+ Kh8 18.Nf5 Bxf5 19.Qxf5 [Threatening Qf6 and Re4.]

19...f6 20.Rad1 [20.Re6!?]

20...cxd5 21.Rxd5 Qxc4 22.Rxd6 Qf7 23.h4 Qh7

The Reliable Petroff

The Petroff (or Russian) Defence which is characterised by the moves 1.e4 e5 2.Nf3 Nf6 has been popular at the highest levels for many years and enjoys the reputation of being an extremely solid defence.

24.Qxh7+ Kxh7 25.Re7+ Kg6?! [Black does not want to settle for a draw. After25...Kg8 26.Rxb7 a5 27.Re6 Na6 28.Ree7 a perpetual ends the game peacefully.]

26.h5+ Kg5 [26...Kxh5? 27.Rg7 and there is no way to defend against Rd3-Rh3. Even after26...Kf5 27.Rd5+ Kf4 28.g3+ Kg4 29.Re4+ Kf3 30.Rdd4 Black is mated.]

27.Rxb7 [27.Rd3!? f5 28.Rg3+ Kf6 29.Rxb7 with better chances for White, as Black has difficulties developing his queenside. 29...Nc6 30.Rg6+ Ke5]

27...a5 28.g3 Ra6 29.Rxb8 [Whites idea.]

29...Rxd630.Rxf8

With an interesting rook ending. Is it winning?

30...Rd2 31.a4 Ra2 32.Kg2 f5 33.Rc8 [33.c4!? withthe idea 33...Rxa4 34.Kh3 Rxc4 35.f4+ Kxh5 36.Rxf5+ Kg6 37.Rxa5]

33...Rxa4 34.Rc5 Ra2 35.Kf3

35... Kf6? [The engines recommend 35...a4 36.g4 Kh4 37.Rxf5 Rc2 38.Ra5 Rxc3+ 39.Kf4 Rc4+ 40.Kf5 Rxg4=]

36.Ke3 Kg5 37.f3 Kxh5 [37...Ra3 38.g4]

38.Kf4 [Threatening Kxf5 and mate afterKf6.]

38...Kg6 39.Rc6+ Kg7 40.Kxf5 [with a decisive advantage.]

40...Rf2 41.Rc7+ Kf8 42.f4 Rf3 43.g4 a4 44.c4 a3 45.Ra7 Rc3 46.Kf6 Ke8 47.c5 Rc4 48.f5 Rxg4 49.c6 Kd8 50.Rxa3 Kc7 51.Rh3 1-0

Sergey Karjakin and Vladislav Artemiev

At the next board, Sergey Karjakin, alsoplaying white, prevailed against Vladislav Artemiev.

The black king is weakened. White has a big advantage.

37.Qe2 Nf5? [Better was 37...Qc5 38.Re6 Ng8 39.Rg6+ Kh8 and Black still holds.]

38.Re6 Qd4 39.Rg6+ Kf8 [39...Kh8 40.Qe8+]

40.Nxf5 Rxf5

Master Class Vol.11: Vladimir Kramnik

This DVD allows you to learn from the example of one of the best players in the history of chess and from the explanations of the authors (Pelletier, Marin, Mller and Reeh) how to successfully organise your games strategically, consequently how to keep y

41.Rxh6 [41.Qc2 wins immediately: 41...Rf7 42.Qc8+ Ke7 43.Re6#]

41...Rf6 42.Rh8+ Kg7 43.Re8 g4 44.Qe7+ Kh6 45.Rh8+ Kg5 46.Rg8+ Kh4 [The king can hardly survive here for long.]

47.g3+ Kh3 48.Qe1 Qd3 49.Re8 a3 50.Re2 Rxf2 51.Qxf2!

[After 51.Rxf2 Qxg3+ 52.Kh1 a2

53.Re2? Black actually has another trick. (53.Qf1+ Kh4 54.Rh2 wins.) 53...a1Q54.Qxa1 Qf3+ 55.Kg1 Qg3+ with perpetual check.]

10

Mikhail Antipovs withdrawal makes for a lopsided tournament. The games he has played count. The remaining games are counted as a win without a fight for the opponent. Fedoseev and Dubov are the most affected. They are relatively high up, despite having given up a halfpoint against Antipov.

1-2. Sergey Karjakin, Ian Nepomniachtchi - 73. Vladimir Fedoseev - 64-5. Maksim Chigaev, Daniil Dubov - 56-8. Vladislav Artemiev, Peter Svidler, Nikita Vitiugov - 59. Andrey Esipenko - 410. Maxim Matlakov - 411. Aleksey Goganov - 312. Mikhail Antipov - 2

Polina Shuvalova suffered a few setbacks after her explosive start, including a loss to Alisa Galliamova in Round 8. Shuvalova facedAleksandra Goryachkina in the penultimate day of competition. Runner-up Goryachkina is the ratingfavourite to win the title and was the leaders closest pursuer, standing a halfpoint behind Shuvalova.

But with one round to go, Goaryachkina did not dare to attack her young opponent. The game between the two contenders for first place was over shortly after the start. Third-placedLeya Garifullinaalso signed a draw. Marina Guseva caught up with Garifullina with a win over Alexandra Kosteniuk.

1. Polina Shuvalova - 72. Aleksandra Goryachkina - 73-4. Marina Guseva, Leya Garifullina - 65. Alisa Galliamova - 66-7. Alexandra Kosteniuk, Alina Kashlinskaya - 58. Natalija Pogonina - 59-10. Olga Girya, Valentina Gunina - 311. Tatyana Getman - 212. Yulia Grigorieva - 1

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Superfinals: Nepomniachtchi and Karjakin still tied on top - Chessbase News

12/4/2020 Can the performance of world class players at online tournaments be used as an indicator for the quality of work done from home? Three economists, among them German IM Dr. Christian Seel, do think so. A report by Stefan Lffler highlights their sobering conclusions. | Image: Christian Seel (private)

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When the pandemic struck in spring, Christian Seel began playing online more frequently. He soon got the impression that he was making more mistakes while playing on a screen than he did on a real board, and wondered whether other players felt the same. When the Magnus Carlsen Chess Tour began in April, Seel followed the games of the world's best players and knew he was onto something.

Among chess players Seel is best known from the Bundesliga, where he plays on board one for the SK Aachen. However, Seel is also a professor of microeconomics at Maastricht University. He is not the only chess enthusiast in his faculty. There is alsoemployment market researcher Stefan Knn, who just recently proved that a higher concentration of particulate matter in the air increases the probability of errors during games of chess.

In call centers or banks, it is expensive or even impossible to reliably assessthe quality of services. Chess games, on the other hand, can be analysed very efficiently with engines.

Dainis Zegners of the Rotterdam School of Management, a colleague and fellow chess enthusiast of Seel and Knn, wasinvolved in their research. At the time, Zegners was working on a different study, which also used chess data. Said study relates to the notion that work is becoming increasingly more challenging from a cognitive standpoint. How does our cognitive performance develop over the course of our lives, and how do different generations compare in this regard? Error quotas in chess games are easy to evaluate, which is why Zegner used them to answer this question.

The three researchers did the same for the games played at the Magnus Carlsen Invitational. As a benchmark, they used games played by the same players at the Rapid World Championships 2015 and 2019, as all these tournaments were played with the same time limit: 15 minutes for the whole and with an additional 10 seconds for each move.

Another important factor from an economic point of view were the incentives offered to the players in the form of prize money, which were at least on a comparable level. This meant that there were a grand total of 27,000 moves to be analysed. This was done with Stockfish, at a search depth of 25 plies.

Seel's personal observation was confirmed. Online, the top players blundered more often than in live games. This held true for every single player for whom data had been available:Magnus Carlsen, Ding Liren, Anish Giri, Alireza Firouzja, Hikaru Nakamura, Ian Nepomniachtchi andMaxime Vachier-Lagrave.

At least Carlsenseems to be sharingthis sentiment. Although he has won amost every single online tournament up to this point, he has also repeatedly criticisedthe quality of his own performance. For one particular tournament, his second Peter Heine Nielsen even rented a holiday lodge to get Carlsen out of "home office mode" and into "tournament-mode".

According to Seel, it is of course plausible to assume that players first need to get used to the new situation. The three authors are considering a follow-up study onwhether performance is going to improve over time, and if so, to what extent. However, Knn, Seel and Zegners first wrote a paper on cognitive performance during work from home. Considering the increased popularity of this approach during the pandemic, their work understandably managed to strike a chord. Their findings were picked up numerous times by the Dutch press.

By the way: Next Sunday, December 6, Christian Seel and Dainis Zegners will be discussing their chess research at the online conference ChessTech 2020. Their session will be preceded by a joint introductory lecture by Fernand Gobet and Andrea Brancaccio, titled "Using chess databases to answer psychological questions: Asurvey".

Translation from German: Hugo B. Janz

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Online Chess and Working from Home - Chessbase News