4,913 research outputs found
Separable and Low-Rank Continuous Games
In this paper, we study nonzero-sum separable games, which are continuous
games whose payoffs take a sum-of-products form. Included in this subclass are
all finite games and polynomial games. We investigate the structure of
equilibria in separable games. We show that these games admit finitely
supported Nash equilibria. Motivated by the bounds on the supports of mixed
equilibria in two-player finite games in terms of the ranks of the payoff
matrices, we define the notion of the rank of an n-player continuous game and
use this to provide bounds on the cardinality of the support of equilibrium
strategies. We present a general characterization theorem that states that a
continuous game has finite rank if and only if it is separable. Using our rank
results, we present an efficient algorithm for computing approximate equilibria
of two-player separable games with fixed strategy spaces in time polynomial in
the rank of the game
On the convergence problem in Mean Field Games: a two state model without uniqueness
We consider N-player and mean field games in continuous time over a finite
horizon, where the position of each agent belongs to {-1,1}. If there is
uniqueness of mean field game solutions, e.g. under monotonicity assumptions,
then the master equation possesses a smooth solution which can be used to prove
convergence of the value functions and of the feedback Nash equilibria of the
N-player game, as well as a propagation of chaos property for the associated
optimal trajectories. We study here an example with anti-monotonous costs, and
show that the mean field game has exactly three solutions. We prove that the
value functions converge to the entropy solution of the master equation, which
in this case can be written as a scalar conservation law in one space
dimension, and that the optimal trajectories admit a limit: they select one
mean field game soution, so there is propagation of chaos. Moreover, viewing
the mean field game system as the necessary conditions for optimality of a
deterministic control problem, we show that the N-player game selects the
optimizer of this problem
Continuous-time integral dynamics for Aggregative Game equilibrium seeking
In this paper, we consider continuous-time semi-decentralized dynamics for
the equilibrium computation in a class of aggregative games. Specifically, we
propose a scheme where decentralized projected-gradient dynamics are driven by
an integral control law. To prove global exponential convergence of the
proposed dynamics to an aggregative equilibrium, we adopt a quadratic Lyapunov
function argument. We derive a sufficient condition for global convergence that
we position within the recent literature on aggregative games, and in
particular we show that it improves on established results
On imitation dynamics in potential population games
Imitation dynamics for population games are studied and their asymptotic
properties analyzed. In the considered class of imitation dynamics - that
encompass the replicator equation as well as other models previously considered
in evolutionary biology - players have no global information about the game
structure, and all they know is their own current utility and the one of fellow
players contacted through pairwise interactions. For potential population
games, global asymptotic stability of the set of Nash equilibria of the
sub-game restricted to the support of the initial population configuration is
proved. These results strengthen (from local to global asymptotic stability)
existing ones and generalize them to a broader class of dynamics. The developed
techniques highlight a certain structure of the problem and suggest possible
generalizations from the fully mixed population case to imitation dynamics
whereby agents interact on complex communication networks.Comment: 7 pages, 3 figures. Accepted at CDC 201
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