3 citations · 3 across the 8 of their papers we have counts for
8 papers
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 finite-horizon approximation of an infinite-horizon feedback Nash equilibrium in discrete-time LQ games
Shengyuan Huang, Xiaoguang Yang, Yifen Mu +1
Computing feedback Nash equilibria (FNEs) in infinite-horizon discrete-time linear-quadratic (LQ) dynamic games remains computationally challenging. Inspired by model predictive co…
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…
An Optimal Pricing Formula for Smart Grid based on Stackelberg Game
Jiangjiang Cheng, Ge Chen, Zhouming Wu +1
The dynamic pricing of electricity is one of the most crucial demand response (DR) strategies in smart grid, where the utility company typically adjust electricity prices to influe…
Periodicity in Hedge-myopic system and an asymmetric NE-solving paradigm for two-player zero-sum games
Xinxiang Guo, Yifen Mu, Xiaoguang Yang
In this paper, we consider the two-payer zero-sum repeated game in which one player (player X) employs the popular Hedge (also called multiplicative weights update) le…
The Optimal Strategy against Hedge Algorithm in Repeated Games
Xinxiang Guo, Yifen Mu
This paper aims to solve the optimal strategy against a well-known adaptive algorithm, the Hedge algorithm, in a finitely repeated zero-sum game. In the literature, rel…