Best experienced payoff dynamics and cooperation in the Centipede game
Segismundo Izquierdo () and
Luis Izquierdo ()
Theoretical Economics, 2019, vol. 14, issue 4
We study population game dynamics under which each revising agent tests each of his strategies a fixed number of times, with each play of each strategy being against a newly drawn opponent, and chooses the strategy whose total payoff was highest. In the Centipede game, these best experienced payoff dynamics lead to cooperative play. When strategies are tested once, play at the almost globally stable state is concentrated on the last few nodes of the game, with the proportions of agents playing each strategy being largely independent of the length of the game. Testing strategies many times leads to cyclical play.
Keywords: Evolutionary game theory; backward induction; Centipede game; computational algebra (search for similar items in EconPapers)
JEL-codes: C72 C73 (search for similar items in EconPapers)
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