Gaming Blog

Review of Seven Games: A Human History by Oliver Roeder

Review of Seven Games: A Human History by Oliver Roeder

You’ve probably played at least one of the seven games featured: Checkers, Chess, Go, Backgammon, Poker, Scrabble, and Bridge. Roeder chose them in part because of their longevity. An early version of checkers is mentioned in Plato”Republicand a prototype backgammon was found in a third-century Nubian tomb (in comparison, Scrabble, invented during the Great Depression, is the relative newcomer).

Each game has its own biographical chapter that explores what makes it unique. An overview of the rules of the game and the skills needed to win are also included. We learn about gaming legends like the humble and devout Marion Tinsley, who has lost just three times in 40 years of competitive checkers. Roeder himself competes in the World Series of Poker and the Scrabble Players Championship, for which he memorizes nearly 35,000 words.

The real benefit of the group biography concept – the connective tissue that ties the book together – is how Roeder illustrates the impact these games have had on artificial intelligence. It goes to the heart of what makes games so valuable, both to humans and to computers.

Games allow humans to make decisions and experience free will within a limited context. As Rice University philosopher Gwen Bradford observes, “Every time you play a game, you choose to do something that is more difficult than necessary.” When we strive and find solutions, it gives us a strong sense of accomplishment (hence the appeal of Wordle).

More precisely, the games consist of arbitrarily imposed games rules. Following these rules allows us to practice making choices and solving problems in a controlled environment. Which also makes it a perfect tool for teaching computers how to think.

Roeder has organized the chapters of his book according to “a rough menu of intelligence” which corresponds – roughly – to the difficulty of computer programs in mastering each game. This classification is based on the complexity of each game, the range of skills required and the element of luck. So checkers, the simplest and theoretically “easiest” (but deeper than you might think) game comes first, while Scrabble, which Roeder memorably describes as a sort of “heptathlon smart”, is sixth.

Surprisingly enough, the famous brain chess game is only second. Although infinitely complicated for humans, chess is not a terrible challenge for a computer program with sufficient processing speed. Armed only with the rules of the game and no other human intervention, AlphaZero, the best chess program in the world, has played itself 44 million times and discovered for itself the Queen’s Gambit, the English opening and the Sicilian defence.

The brilliance of the world’s highest ranked human chess player, Magnus Carlsen, pales in comparison to computer-generated competitors. Over 90 computer engines are ranked higher than Carlsen. To verify Best Chess Engine Championship watch elite computer programs perform at a level humans have never matched.

Because they are entirely governed by rules, checkers, chess, and go can all be mastered by computers. But that doesn’t mean they are simple. Ladies alone have 500,995,484,682,338,627,639 different positions. The number of positions for the infinitely more complex Go is so immense that it has 171 digits. For comparison, Roeder tells us that the number of atoms in the entire universe is an 80-digit number.

Still, as daunting as those numbers are, adding an element of luck is a real game-changer (pardon the pun). Computers lose their edge over humans when they play a completely random game like rock, paper, scissors. In backgammon, poker and Scrabble, the roll of the dice, or the drawing of a card or tile, introduces a level of chance that makes it exponentially more difficult for humans or computers to predict the next move. It’s just not possible (yet) to use raw computing power to wade through huge decision tree branches and choose the best options. Machines can tackle certain aspects of the game, but they cannot solve it.

This forces scientists to find new ways to exploit the enormous potential of computing. For backgammon, IBM researcher Gerald Tesauro created a neural network program that looked for patterns instead, mimicking human learning. Not only did TD-Gammon, as he named his program, come to dominate the backgammon scene, it has gone on to provide tangible benefits in a variety of other applications such as elevator traffic in high-rise buildings. and work planning for the space shuttle.

As computers improved their game, so did humans, who now study their games and learn from commercial and free programs such as eXtreme Gammon, PokerSnowie and Quackle. This has helped democratize gaming. You no longer have to live in certain places, or have the means to travel, play and study a game at the highest level. You can just go online or check an app on your phone. This is especially true in poker, where the wide availability of programs known as solvers are helping a new generation of would-be pros pursue optimal betting strategies.

But there can be downsides. The colorful, larger-than-life poker players with big hats and jewelry are slowly being replaced by guys in sunglasses and headphones who don’t interact with anyone at the table. They may be more successful, but they’re no fun. Traditionalists fear that if the social aspect of gambling wanes, so will the enthusiasm of casual gamblers who trust their luck and lose enough to bankroll the winners.

Bridge, the last game and the one Roeder describes as “the most ‘human'”, is perhaps the most complex from a skill perspective (it even has its own special auction languages). It’s also the only game of sevens where artificial intelligence programs still track human players.Although its popularity has dropped dramatically since its peak in the 1930s and 1940s, being good at bridge is still seen by many on Wall Street as a predictor success in the real world.Today, bridge tournaments are subsidized by ultra-rich patrons who sponsor teams for bragging rights, much like other wealthy people might sponsor a racehorse or a racing sailboat .

Like the games it features, “Seven Games” is accessible, enjoyable, and ultimately quite challenging. It raises provocative and sometimes troubling questions about the nature of intelligence and the unintended consequences when machines play better than us. Roeder makes many wise observations but offers no answers, just philosophical paths to follow. If you’re intrigued by this rare opportunity to pull back the curtain on how humans and computers learn, then you’ll be richly rewarded. You could also improve your game.