4,574 research outputs found
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
Distributed Learning for Stochastic Generalized Nash Equilibrium Problems
This work examines a stochastic formulation of the generalized Nash
equilibrium problem (GNEP) where agents are subject to randomness in the
environment of unknown statistical distribution. We focus on fully-distributed
online learning by agents and employ penalized individual cost functions to
deal with coupled constraints. Three stochastic gradient strategies are
developed with constant step-sizes. We allow the agents to use heterogeneous
step-sizes and show that the penalty solution is able to approach the Nash
equilibrium in a stable manner within , for small step-size
value and sufficiently large penalty parameters. The operation
of the algorithm is illustrated by considering the network Cournot competition
problem
Generalized Stochastic Dynamic Aggregative Game for Demand-Side Management in Microgrids with Shared Battery
In this paper, we focus on modeling and analysis of demand-side management in
a microgrid where agents utilize grid energy and a shared battery charged by
renewable energy sources. We model the problem as a generalized stochastic
dynamic aggregative game with chance constraints that capture the effects of
uncertainties in the renewable generation and agents' demands. Computing the
solution of the game is a complex task due to probabilistic and coupling
constraints among the agents through the state of charge of the shared battery.
We investigate the Nash equilibrium of this game under uncertainty considering
both the uniqueness of the solution and the effect of uncertainty on the
solution. Simulation results demonstrate that the presented stochastic method
is superior to deterministic methods
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