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Riemannian game dynamics
[article]
2018
arXiv
pre-print
We study a class of evolutionary game dynamics defined by balancing a gain determined by the game's payoffs against a cost of motion that captures the difficulty with which the population moves between states. Costs of motion are represented by a Riemannian metric, i.e., a state-dependent inner product on the set of population states. The replicator dynamics and the (Euclidean) projection dynamics are the archetypal examples of the class we study. Like these representative dynamics, all
arXiv:1603.09173v3
fatcat:ic7ginobw5adlc36ad2qcj5fjm