5 papers
On finite-horizon approximation of an infinite-horizon feedback Nash equilibrium in discrete-time LQ games
Shengyuan Huang, Xiaoguang Yang, Yifen Mu +1
In infinite-horizon discrete-time linear-quadratic (LQ) dynamic games, computing feedback Nash equilibria (FNEs) remains computationally challenging. Motivated by this, we study a…
Robust Aggregation of Calibrated Forecasts
Xinxiang Guo, Yingkai Li, Yifen Mu
Decision-makers often rely on multiple probabilistic forecasts that are individually calibrated but need not be fully informative. We develop a framework for aggregating such forec…
Decentralized MARL for Coarse Correlated Equilibrium in Aggregative Markov Games
Siying Huang, Yifen Mu, Ge Chen
This paper studies the problem of decentralized learning of Coarse Correlated Equilibrium (CCE) in aggregative Markov games (AMGs), where each agent's instantaneous reward depends…
Private Markovian Equilibrium in Stackelberg Markov Games for Smart Grid Demand Response
Siying Huang, Yifen Mu, Ge Chen
The increasing integration of renewable energy introduces a great challenge to the supply and demand balance of the power grid. To address this challenge, this paper formulates a S…
On the convergence of fictitious play algorithm in repeated games via the geometrical approach
Zhouming Wu, Yifen Mu, Xiaoguang Yang
As the earliest and one of the most fundamental learning dynamics for computing NE, fictitious play (FP) has being receiving incessant research attention and finding games where FP…