How to succeed at Rock-Paper-Scissors

rockpaperscissors

Would you believe me if I told you there’s a scientific publication concerning the psychology of Rock-Paper-Scissors? No?

Surprise! There actually is one, entitled “Social cycling and conditional responses in the Rock-Paper-Scissors game” by Zhijan Wang et al.

Basically, the authors took 6 groups of 60 students each, and had them play 300 rounds of the game in random pairings. Using complicated mathematical calculations and models, they actually found some interesting patterns. For example, whenever a student won using a particular action, the likelihood that they repeated that same action in the following round greatly increased.  Moreover, when a student lost, they were more likely to play the action that would have beaten the one they just lost to. They called these phenomena “win-stay” and “lose-switch”, respectively.

So what can this data tell us about our frequent “best out of 3” tournaments? Personally, I think it explains why so many second rounds end up being ties. My theory aside, the truth is the students in this study had random opponents that changed each round. When playing against the same person, the psychology would probably change. But then again, it might not. After all, I specialize in cells, not people, so I could be wrong. Ultimately, the authors weren’t really interested in helping the average person win at Rock-Paper-Scissors, they were interested in how the mathematical models they created can be used in “game theory”, the science of decision-making.

So can we truly beat the system? Probably not, but it’s always fun to think that we can!

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4 responses to “How to succeed at Rock-Paper-Scissors

  1. My theory would be that “win-stay” and “lose-switch” would occur less often when playing with random opponents, because each round is a fresh start with less carry-over from the previous round. However, since we still saw these phenomena with random opponents, there probably isn’t much difference between playing against the same person vs random opponent.

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  2. I also would expect that any cognitive bias would be exaggerated when playing with the same opponent. There have been several algorithmic approaches to win RPS vs humans based on that. NYT made a cool app where the AI uses the last four moves to predict your next move here: http://www.nytimes.com/interactive/science/rock-paper-scissors.html

    Extending the algorithmic approach, rpscontest.com lets people submit their own algorithms and ranks how people do when playing against them. http://www.rpscontest.com/leaderboard. One top ranked algorithm from a different contest is explained here: http://dan.egnor.name/iocaine.html

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    • Thanks for the links and insight! I guess my moves must be particularly easy to predict, because I lost 9 out of 10 rounds to that stupid robot! *shakes fist*

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