An overview of multi-agent reinforcement learning from game theoretical perspective
Y Yang, J Wang - arXiv preprint arXiv:2011.00583, 2020 - arxiv.org
Following the remarkable success of the AlphaGO series, 2019 was a booming year that
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
Mean field games and applications: Numerical aspects
The theory of mean field games aims at studying deterministic or stochastic differential
games (Nash equilibria) as the number of agents tends to infinity. Since very few mean field …
games (Nash equilibria) as the number of agents tends to infinity. Since very few mean field …
Deep generalized schrödinger bridge
Abstract Mean-Field Game (MFG) serves as a crucial mathematical framework in modeling
the collective behavior of individual agents interacting stochastically with a large population …
the collective behavior of individual agents interacting stochastically with a large population …
[图书][B] The master equation and the convergence problem in mean field games:(ams-201)
P Cardaliaguet, F Delarue, JM Lasry, PL Lions - 2019 - books.google.com
This book describes the latest advances in the theory of mean field games, which are
optimal control problems with a continuum of players, each of them interacting with the …
optimal control problems with a continuum of players, each of them interacting with the …
[图书][B] Probabilistic theory of mean field games with applications I-II
The lion's share of this chapter is devoted to the construction of equilibria for mean field
games with a common noise. We develop a general two-step strategy for the search of weak …
games with a common noise. We develop a general two-step strategy for the search of weak …
Mean field games
PE Caines - Encyclopedia of systems and control, 2021 - Springer
The notion of the infinite population limit of large population games where agents are
realized by controlled stochastic dynamical systems is introduced. The theory of infinite …
realized by controlled stochastic dynamical systems is introduced. The theory of infinite …
Probabilistic analysis of mean-field games
The purpose of this paper is to provide a complete probabilistic analysis of a large class of
stochastic differential games with mean field interactions. We implement the Mean-Field …
stochastic differential games with mean field interactions. We implement the Mean-Field …
Mean field games and systemic risk
We propose a simple model of inter-bank borrowing and lending where the evolution of the
log-monetary reserves of $ N $ banks is described by a system of diffusion processes …
log-monetary reserves of $ N $ banks is described by a system of diffusion processes …
Forward–backward stochastic differential equations and controlled McKean–Vlasov dynamics
The purpose of this paper is to provide a detailed probabilistic analysis of the optimal control
of nonlinear stochastic dynamical systems of McKean–Vlasov type. Motivated by the recent …
of nonlinear stochastic dynamical systems of McKean–Vlasov type. Motivated by the recent …