An N-coalition noncooperative game is formulated in this paper. In the formulated game,
there are N interacting coalitions and each of them includes a set of agents. Each coalition …

Stochastic Averaging and Extremum Seeking treats methods inspired by attempts to
understand the seemingly non-mathematical question of bacterial chemotaxis and their …

There is a growing interest in the application of game theoretic methods to the design and
control of multiagent systems. However, the existing game theoretic framework possesses …

Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has
led to a dramatic increase in the number of applications and methods. Recent works have …

We consider a Cartesian stochastic variational inequality problem with a monotone map.
Monotone stochastic variational inequalities arise naturally, for instance, as the equilibrium …

We study the performance of the gradient play algorithm for stochastic games (SGs), where
each agent tries to maximize its own total discounted reward by making decisions …

A distributed model predictive control (DMPC) framework is proposed. The physical plant
structure and the plant mathematical model are used to partition the system into self …

Due to their broadcast nature, wireless networks are highly susceptible to jamming attacks
resulting in denial of service. Game theory provides powerful tools to model and analyze …

We design a distributed algorithm for learning Nash equilibria over time-varying
communication networks in a partial-decision information scenario, where each agent can …

This paper examines a stochastic formulation of the generalized Nash equilibrium problem
where agents are subject to randomness in the environment of unknown statistical …