The child’s game rock-scissors-paper is designed for a random outcome in which no player has an advantage over any other.
While that might be true based solely on random probability, it ignores the way humans actually play the game, according to a new study published by Cornell University.
At a rock-paper-scissors tournament at China’s Zhejiang University, scientists recruited 360 students, placed them in groups of six and had each of them run 300 rounds against their fellow group members. As an incentive, winners were paid for each individual victory.
At first, the results appeared completely random — rock, paper or scissors were each chosen one-third of the time.
But on closer examination, the scientists found a pattern:
When a player won a round, he or she was more likely to choose the winning option in the next round.
And if the player lost, he or she tended to choose an easily predicted next option that fell in sequence of the order of the game’s name: rock, then paper, then scissors. For example, if the player lost with rock, he or she was likely to try paper in the next round or if the player lost with paper, he or she tended to play scissors next.
The results seem to defy the Nash equilibrium, a basic tenet of game theory that says players will randomize their choices. It’s named after John Forbes Nash Jr., a pioneer of game theory who was the subject of the 2001 film A Beautiful Mind, with actor Russell Crowe portraying the troubled genius Nash.
As the BBC notes, “This ‘win-stay lose-shift’ strategy is known in game theory as a conditional response — and it may be hard-wired into the human brain, the researchers say.” It adds:
“Anticipating this pattern – and thereby trumping your opponent – ‘may offer higher pay-offs to individual players’ they write.
“The game of rock-paper-scissors exhibits collective cyclic motions which cannot be understood by the Nash equilibrium concept.
“‘Whether conditional response is a basic decision-making mechanism of the human brain or just a consequence of more fundamental neural mechanisms is a challenging question for future studies.”
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