After a game, CUBE Backgammon shows the winner alongside estimates of who played better and whom the dice favoured. Building that analysis forces us to ask what separating luck from skill can actually mean in a single game.
Some Roman gaming boards had 36 playing spaces, arranged as six words of six letters. By the fifth century, the Byzantine emperor Zeno was playing on a board with the familiar 24 points, though he used three dice.
We do occasionally think about something other than backgammon, as long as it still involves two dice. The puzzle below is about probability rather than backgammon strategy. “Double, double, non-double” and “non-double, double, double” are equally likely in three preselected rolls. Keep rolling until either appears, however, and the second pattern wins with probability 35/36.
Two ways of playing the same 3–2 leave the same pip count, but different opportunities next turn. In our example, one arrangement lets 15 of the 36 rolls make a new point while keeping the existing ones; the other allows only five.
Our order is blackjack, English checkers, backgammon, chess, Go, then full partnership bridge. The surprises are what dice do to backgammon’s search, why Go resisted position evaluation, and how hidden cards complicate bridge.
Building a backgammon engine raises a tempting question: how much can you settle by simulating more games? Bridge, a game my grandfather played brilliantly, shows why a simulation must also respect what the player can know.
Jeremy Bagai thought he had mastered backgammon within a week. Twelve years later, he published his own book correcting mistakes in five influential books he had learned from, written by authors such as Paul Magriel and Bill Robertie.
When a comeback looks unlikely, bearing off just one checker can prevent a double or triple loss, but abandoning a good chance to hit can also be expensive.
With a checker on the bar and a 6–1 to play, entering with the one can leave the six unusable. If the other order lets you play both dice, the rules require you to use it.
At 0–0, a chance to win two or three points can be worth taking a small risk. At 6–6 in a match to seven, one point already wins the match. The same board can call for a different move.
Your opponent makes an anchor, and the checker you wanted to attack is suddenly protected. Follow that change on the board, then explore when to attack, block, run or wait.
Taking a double can put the whole match on one position, while passing leaves another route through the games that follow. A small bear-off example shows how those chances compare.
Our backgammon engine cannot follow every possible game to its ending. It needs a useful estimate of what each unfinished position is worth, so it can compare the moves that lead there. That estimate is at the centre of its decisions.
For an ordinary computer match, CUBE Backgammon generates the dice sequence from a random starting value before the first roll. After the match, you can reproduce the sequence and check that the recorded rolls match it.
To improve CUBE Backgammon’s move advice, we trained the neural network that evaluates backgammon positions on more examples. It agreed more often with its teaching engine, GNU Backgammon, but chose worse moves in a separate test that played out possible continuations.
To check whether a development version of CUBE Backgammon chose better moves, we asked Open Sage, another backgammon engine, to evaluate them. On half the positions, our code supplied the wrong player to roll and distorted the comparison.
Our tests against GNU Backgammon provide evidence about CUBE Backgammon’s checker play. Here is what those results show and what we would need to compare the engine with professional players.
We tested a development version of CUBE Backgammon’s coach on recorded tournament play. A second engine found that some suggested corrections were worse than the moves the players had made.
7 articles
Culture & history
The words, places and traditions that travel with the game.
The dice that frustrate backgammon players also helped an early neural network learn the game. They carried its practice games into new positions, giving a program playing against itself more varied experience.
When we compare moves in CUBE Backgammon, we need to consider both future dice and an opponent who chooses how to use them. Blackjack keeps the uncertain cards but fixes the dealer’s behaviour, which changes the calculation considerably.
In the 1990s, computers transformed how people played backgammon, a game with centuries of history. Programs that could simulate thousands of games prompted leading players to rethink long-established advice, even about the opening moves.
A poem records a Byzantine emperor rolling 2, 5 and 6 and ending up with eight exposed checkers. Reconstructing the position shows how the roll forced him to break all three of his pairs.
When archaeologists excavated the Mary Rose, an English warship from Henry VIII’s navy that sank in 1545, they found a backgammon set among the tools in its carpenter’s cabin.
Some players in the backgammon boom of the 1920s and 1930s tracked doubles with ordinary matchsticks. Period guides show why they needed to agree on what each match meant, while a 1930 advertisement offers a more compact solution.
Some backgammon players in the Arab world and Turkey call the dice with words inherited from Persian, sometimes mixed with Turkish. A six and a five make a particularly good example.