Solution to God-Einstein-Oppenheimer Dice Puzzle
The God-Einstein-Oppenheimer Dice Puzzle fooled a lot of overconfident readers, but it also prompted an extraordinary burst of problem solving. Lab readers didn’t just figure out who would win God’s dice game between Einstein and J. Robert Oppenheimer. You did calculations, created spreadsheets and ran computer simulations to figure out the best possible strategy. You wrote some great dialogue for God, Einstein, Oppenheimer (and Nietzsche, making a guest appearance). You even provided a simulator to play the game.
The prize, a copy of Marcel Danesi’s puzzle book, “The Total Brain Workout,” goes to Pradeep Mutalik for his many accomplishments. Dr. Mutalik, a scientist at the Center for Medical Informatics at Yale, wrote philosophical dialogue for God and dice players and and sifted through the nearly 300 answers to provide a meta-analysis of the responses and of the methods of solution. And he submitted a new puzzle, which I’ll present in a later post today.
If you still want to try the puzzle yourself, click here. Keep reading if you want the solution.
The solution: Oppenheimer can always win by turning this into a dice version of Rock, Paper, Scissors. He can number the dice so that Die A beats Die B, and B beats C, but C beats A. Thus, whichever die Einstein chooses, Oppenheimer can choose another die that will beat it. Dave provided a quick illustration of how the odds work in one such arrangement.
Exactly how would Oppenheimer do this, and what would be the best odds he could give himself against Einstein? Here’s Dr. Mutalik’s analysis of how Lab readers solved the puzzle:
It has been established that Oppenheimer can always win by creating a set of non-transitive (Rock, Scissors, Paper) dice where A beats B, B beats C and C beats A. But how does Oppenheimer create such sets of dice?
Here are the methods that have been employed:
1) Trial and error. Good luck, and hope that God is with you (you’d better be Oppenheimer, not Einstein). Your chances of finding a nontransitive set are about 0.37 percent, or about 1 in 300. Not quite a needle in a haystack, but not a walk in the park either!
2) The cyclic method. This is simple and creates dice that have a pleasing symmetry. An example is to divide the 18 numbers into 6 sets of triplets in order (1,2,3…4,5,6…) and then assign the high, middle and low members of each triplet cyclically to dice A, B and C (ABC, BCA, CAB etc).
This method was first elucidated by lilnev. It was presented in elegant visual form by aDUB, whose success in printing his or her scheme, after multiple attempts using the limited formatting tools for posting responses, is indeed commendable.
The drawback of the cyclical method is that the payoff is not the highest. It is 19/36.
3) The “fiddling with equals” method: Here you create three dice that score evenly and then swap numbers between adjacent ones to allow one to beat the other without affecting the third. Repeat the procedure for the other two pairs.
This method was first elaborated by Metalate.
4) The “double and redundant” approach. You start by creating a cyclic set for three-sided dice, which is easy enough. Then, for the six-sided dice, you double the numbers and assign the additional adjacent lower odd numbers to the same die, thus rendering them redundant and effectively using the same solution!
This method was first pointed out by Robert. It gives a payoff of 20/36, which is better than the cyclic methods. I confess this method is my favorite.
Of course there are other ways to find solutions in modern times, with Google, Wikipedia and brute-force computer search. But that’s cheating, unless you solved the problem the old-fashioned way first!
The second big question is: How does Oppie maximize his payoff? The maximum payoff is 21/36. There are only 15 such sets of dice among the 10,705 solutions.
As far as I can tell, the first one who came up with a set of dice with this payoff was Nathan Penton. In retrospect, his post is hilariously ironic. After giving his solution (the first one listed below), he said: “I guarantee there are better solutions that give O a bigger edge. I apologize for not finding the general solution.” But it turns out that his solution is the very BEST solution out of all 10,705 (payoff 21 with one of the scores being 25)! Did he find the needle in the haystack, or was he just being modest?
Is there a method that generates these 15 and only these 15, without recourse to a brute-force search? I don’t know. It would make a nice math project. Henrik Rummel, whose paper, “The Paradox of Nontransitive Dice,” was referred to by some posters, proved a theorem that gives the upper bound for the payoff for any set of nontransitive dice of this type. For three six-sided dice it turns out to be 22.25. But there are no sets that have a payoff of 22, and the paper does not contain any analytical methods for generating optimal sets.
For the sake of completeness, here are all 15 solutions that have a payoff of 21/36. Maybe someone can design a simple method to find them.
A:5,6,7,8,9,18 B:2,3,4,15,16,17 C:1,10,11,12,13,14
Scores: 21,21,25
A:5,6,7,8,10,18 B:2,3,4,15,16,17 C:1,9,11,12,13,14
Scores: 21,21,24
A:5,6,7,9,10,18 B:2,3,4,15,16,17 C:1,8,11,12,13,14
Scores: 21,21,23
A:5,6,7,8,11,18 B:2,3,4,15,16,17 C:1,9,10,12,13,14
Scores: 21,21,23
A:5,6,8,9,10,18 B:2,3,4,15,16,17 C:1,7,11,12,13,14
Scores: 21,21,22
A:5,6,7,9,11,18 B:2,3,4,15,16,17 C:1,8,10,12,13,14
Scores: 21,21,22
A:5,6,7,8,12,18 B:2,3,4,15,16,17 C:1,9,10,11,13,14
Scores: 21,21,22
A:6,7,8,11,12,13 B:3,4,5,10,17,18 C:1,2,9,14,15,16
Scores: 21,21,21
A:6,7,8,9,10,17 B:3,4,5,14,15,16 C:1,2,11,12,13,18
Scores: 21,21,21
A:3,4,5,14,15,16 B:2,9,10,11,12,13 C:1,6,7,8,17,18
Scores: 21,21,21
A:5,7,8,9,10,18 B:2,3,4,15,16,17 C:1,6,11,12,13,14
Scores: 21,21,21
A:5,6,8,9,11,18 B:2,3,4,15,16,17 C:1,7,10,12,13,14
Scores: 21,21,21
A:5,6,7,10,11,18 B:2,3,4,15,16,17 C:1,8,9,12,13,14
Scores: 21,21,21
A:5,6,7,9,12,18 B:2,3,4,15,16,17 C:1,8,10,11,13,14
Scores: 21,21,21
A:5,6,7,8,13,18 B:2,3,4,15,16,17 C:1,9,10,11,12,14
Scores: 21,21,21
Congratulations to Jake for being the first Lab reader to name Oppenheimer the winner, to Adam S. for providing the first solution, and to Mark Nelson for coming up with the 15 optimal solutions (giving Oppenheimer a 21 of 36 chance of winning). Kudos to Andrew for writing a computer program to do a complete analysis, and to TheOrpheus for creating the simulator.
And thanks again to Dr. Mutlalik for his meta-analysis.
The only issue with these problems is this thing called google. When you want to take time to think, you realize you’re “competing” against people who are busily going through google searches for the answers. It’s almost like we need an honor code.