Friday, 15:45 - 16:10 h, Room: MA 005


Angelia Nedich
A gossip algorithm for aggregative games on graphs

Coauthors: Jayash Koshal, Uday V. Shanbhag


We consider a class of games, termed as aggregative games, being played over a distributed
multi-agent networked system. In an aggregative game, an agent's objective
function is coupled through a function of the aggregate of all agents decisions. Every
agent maintains an estimate of the aggregate and agents exchange this information
over a connected network. We study the gossip-based distributed algorithm for information
exchange and computation of equilibrium decisions of agents over the network.
Our primary emphasis is on proving the convergence of the algorithm under an assumption
of a diminishing (agent-specific) stepsize sequence. Under standard conditions,
we establish the almost-sure convergence of the algorithm to an equilibrium point. Finally,
we present numerical results to assess the performance of the gossip algorithm
for aggregative games.


Talk 2 of the invited session Fri.3.MA 005
"Learning and computation for game-theoretic problems" [...]
Cluster 8
"Game theory" [...]


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