JOSEF LUNDIN
Josef Lundin is a sophomore Biology student at Wilkes University. He was born and raised in Alberta, Canada where he first began wrestling in middle school. Josef later translated his love for wrestling into a career where he now wrestles at Wilkes university on top of his studies.
First emerging in Spain in the 15th century, chess is a transcendental strategy game to which two players move distinct pieces along an 8×8 board in an attempt to capture their opponent’s king. As time moved forward so did the game and as such emerged many philosophies as to how one should strategies their play. The one true fault of this evolution in play however; was the fact that people could only strategise so far ahead due to the lack of processing power the human mind contains and in turn this led to a drought of progress. Then came computers and AI and with this new technology that could see infinite possibilities this led to a golden age of chess with new and exciting strategies that had been for many centuries overlooked. Through the use of modern technologies and AI, some of the greatest modern chess players have not only been able to excel past their opponents but also evolve and change the way the game is played.
When AI was first introduced into chess it was significantly limited by the technology that was available at the time, this limitation was largely partitioned of processing power of computers during that time. In one such study it explains, “Technical advances accelerated progress in computer chess during the 1970s and ’80s. Sharp increases in computing power enabled computers to “see” much further. Computers of the 1960s could evaluate positions no more than two moves ahead, but authorities estimated that each additional half-move of search would increase a program’s performance level by 250 rating points.” (“Chess – Chess and Artificial Intelligence”). Deep Blue, one of the first and most notorious chess AI’s to be conceived. Deep Blue was the predecessor of Deep Thought which first made its appearance in 1988 and could, for the time, see a remarkable 2 moves ahead. With Deep Blue being the upgrade, “ [it] made its debut in a six-game match with PCA champion Kasparov in February 1996.” (“Chess – Chess and Artificial Intelligence”). At the time Deep Blue could see an astonishing 6 moves ahead with Kasparov claiming that he himself could only see approximately 3 to 5 moves ahead. In their match Deep Blue managed to secure the first win through tactical play; however, Kasparov managed to modify his style of play and came back to win the match 4 to 2. Recovering from this loss the team behind Deep Blue remodeled the way the AI computed by taking advice from many other grandmasters of the game and in doing so, “Deep Blue was able to consider an average of 200 million positions per second, twice its previous speed.” (“Chess – Chess and Artificial Intelligence”). A six game rematch between the two was held in 1997 and to many peoples surprise Kasparov had improved exponentially since their last game. By studying how the AI played previously Kasparov was able to become considerably better, but with such aggressive upgrades to Deep Blue Kasparov lost the match with their final game astonishingly being only 19 moves, a blow out. While Kasparov lost this match in such a fashion it ultimately served to illustrate computers and AI could serve useful in the evolution of chess as it was not only able to beat the best player of the time, but dominate him.
Although openings and endgames are imperative dictations of classical and modern chess philosophies, aspects like piece value and castling can be argued to be equally if not more important. Castling is one such option in the game of chess that if done incorrectly can burden the player with a dreadful losing position or an even stronger one that can leave their opponent in shambles. Because of how pivotal a move such as this one can be many have studied its attributes to an unequivocal degree. By using AI the study of this move became even more complex and evolved. In a study by Vladimir Kramnik he found that “Both White and Black castle in most classical chess openings, and removing castling as an option profoundly changes the characteristics of the game.” (Kramnik 63). While it’s unsurprising that classical chess would lead itself more towards games that are inclusive of castling, it is surprising to see that if a player has the ability to remove their opponents castling privileges it changes the game so drastically that modern chess deploys many tactics that utilize this development. Piece value is another aspect of the game that is often argued between player and player. There is much to consider when arguing piece value with one such thing being the position on the board which as discussed earlier can be very complex. In the same study by Kramnik he found, “Looking at the piece value estimates for classical chess, the method approximately recovers known material valuesand identifies bishops as more valuable than knights. Estimates of piece values in No-castling, No-castling (10), Pawn-one-square, Self-capture, and Stalemate = win variants look fairly similar, which is not surprising given the minor differences in piece mobility compared to the other variants. Variants involving an increase in pawn mobility result in lower relative values for other pieces, as can be seen in Pawn-back, Semi-torpedo, Torpedo, and Pawn-sideways. In Pawn-sideways chess, AlphaZero often sees the trade of a knight or bishop for two pawns as favorable, in accordance with this approximation. Such an exchange would normally be considered bad in classical chess. Material values may vary across different game stages and position types, and hence, the values in are merely meant to help new players make sense of tactical exchanges in these chess variants.” (Kramnik 64). Such a combative difference between classical and modern chess only serves to emphasize how impressive the introduction of computer AI to such a primitive game can develop it.
While chess first emerged in the 15th century as a primitive game that was once used to illustrate one’s intelligence, it has evolved to become a competitive game of tactics, deception, and evolution. Deep Blue being among the first to introduce this concept of evolution in the game of chess in its thrilling match with Kasparov and even more intriguing rematch. AI in chess snowballed in such a way that it completely revolutionized the game. Beginning first with the mending of openings and endgames to later more conceptual philosophies like piece value and castling. The introduction of AI has overall made chess a more complete yet complex game that can be enjoyed from the newest of players to the most seasoned grandmasters of the game.
Works Cited
“Chess and Artificial Intelligence.” Encyclopædia Britannica, Encyclopædia Britannica, Inc., https://www.britannica.com/topic/chess/Chess-and-artificial-intelligence.
Menon , Aditya. “The Impact of Artificial Intelligence (AI) and Engines on Boardgames (Chess and Go).” Terra, IJHSR, https://terra-docs.s3.us-east-2.amazonaws.com/IJHSR/Articles/volume4-issue2/2022_42_p65_Menon.pdf.
Kramnik, Vladimir. “AI Is Driving the next Evolution of Chess, Giving Players a Glimpse into the Game’s Future.” Dl, ACM, https://dl.acm.org/doi/fullHtml/10.1145/3460349#body-7.