We study large population stochastic dynamic games where each agent receives influences from multi-classes of agents according to intra- and inter-subpopulation cost coupling. The NCE principle developed in our previous works gave decentralized asymptotic Nash strategies; however, its solubility depends on a conservative fixed point analysis which does not lead to easy computation of the solution. In this paper we apply a different algebraic approach via a state space augmentation, and it is convenient for practical computation involving first a set of algebraic Riccati equations subject to consistency constraints and next a set of ordinary differential equations
The adoption of Nash equilibrium (NE) in real–world set-tings is often impractical due to its too re...
© 2016 Institute of Mathematical Statistics. We propose a new approach to mean field games with majo...
We consider a multi-agent system consisting of several populations. The interaction between large po...
Abstract—We study large population stochastic dynamic games where each agent assigns individually de...
Abstract. We consider stochastic dynamic games in large population conditions where multi-class agen...
Abstract — We consider large population dynamic games and illuminate methodological connections with...
We consider the dynamic optimization of large-population system with partial information. The associ...
Abstract We consider dynamic games in large population conditions where the agents evolve according ...
Abstract We study large population stochastic dynamic games where the so-called Nash certainty equiv...
International audienceAggregative games have many industrial applications, and computing an equilibr...
This paper considers dynamic optimization problems for a class of control average meanfield stochast...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
We consider the framework of aggregative games, in which the cost function of each agent depends on ...
We consider the framework of aggregative games, in which the cost function of each agent depends on ...
Abstract This paper is concerned with decentralized tracking-type games for large popula-tion multi-...
The adoption of Nash equilibrium (NE) in real–world set-tings is often impractical due to its too re...
© 2016 Institute of Mathematical Statistics. We propose a new approach to mean field games with majo...
We consider a multi-agent system consisting of several populations. The interaction between large po...
Abstract—We study large population stochastic dynamic games where each agent assigns individually de...
Abstract. We consider stochastic dynamic games in large population conditions where multi-class agen...
Abstract — We consider large population dynamic games and illuminate methodological connections with...
We consider the dynamic optimization of large-population system with partial information. The associ...
Abstract We consider dynamic games in large population conditions where the agents evolve according ...
Abstract We study large population stochastic dynamic games where the so-called Nash certainty equiv...
International audienceAggregative games have many industrial applications, and computing an equilibr...
This paper considers dynamic optimization problems for a class of control average meanfield stochast...
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
We consider the framework of aggregative games, in which the cost function of each agent depends on ...
We consider the framework of aggregative games, in which the cost function of each agent depends on ...
Abstract This paper is concerned with decentralized tracking-type games for large popula-tion multi-...
The adoption of Nash equilibrium (NE) in real–world set-tings is often impractical due to its too re...
© 2016 Institute of Mathematical Statistics. We propose a new approach to mean field games with majo...
We consider a multi-agent system consisting of several populations. The interaction between large po...