Nonlinear Markov games on a finite state space (mean-field and binary interactions)

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Kolokoltsov, V. N. (Vasiliĭ Nikitich) (2012)

Managing large complex stochastic systems, including competitive interests, when one or several players can control the behavior of a large number of particles (agents, mechanisms, vehicles, subsidiaries, species, police units, etc), say Nk for a player k, the complexity of the game-theoretical (or Markov decision) analysis can become immense as Nk → ∞. However, under rather general assumptions, the limiting problem as all Nk → ∞ can be described by a well manageable deterministic evolution. In this paper we analyze some simple situations of this kind proving the convergence of Nashequilibria for finite games to equilibria of a limiting deterministic differential game.
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