Penalty-regulated dynamics and robust learning procedures in games

9 Mar 2013Pierre CoucheneyBruno GaujalPanayotis Mertikopoulos

Starting from a heuristic learning scheme for N-person games, we derive a new class of continuous-time learning dynamics consisting of a replicator-like drift adjusted by a penalty term that renders the boundary of the game's strategy space repelling. These penalty-regulated dynamics are equivalent to players keeping an exponentially discounted aggregate of their on-going payoffs and then using a smooth best response to pick an action based on these performance scores... (read more)

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