2 citations · 4 across the 8 of their papers we have counts for
9 papers
Offline Learning of Decision Functions in Multiplayer Games with Expectation Constraints
Yuanhanqing Huang, Jianghai Hu
We explore a class of stochastic multiplayer games where each player in the game aims to optimize its objective under uncertainty and adheres to some expectation constraints. The s…
A Bandit Learning Method for Continuous Games under Feedback Delays with Residual Pseudo-Gradient Estimate
Yuanhanqing Huang, Jianghai Hu
Learning in multi-player games can model a large variety of practical scenarios, where each player seeks to optimize its own local objective function, which at the same time relies…
Bandit Online Learning in Merely Coherent Games with Multi-Point Pseudo-Gradient Estimate
Yuanhanqing Huang, Jianghai Hu
Non-cooperative games serve as a powerful framework for capturing the interactions among self-interested players and have broad applicability in modeling a wide range of practical…
Zeroth-Order Learning in Continuous Games via Residual Pseudogradient Estimates
Yuanhanqing Huang, Jianghai Hu
A variety of practical problems can be modeled by the decision-making process in multi-player games where a group of self-interested players aim at optimizing their own local objec…
On the Convergence Rates of A Nash Equilibrium Seeking Algorithm in Potential Games with Information Delays
Yuanhanqing Huang, Jianghai Hu
This paper investigates the equilibrium convergence properties of a proposed algorithm for potential games with continuous strategy spaces in the presence of feedback delays, a mai…
Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters
Yuanhanqing Huang, Jianghai Hu
In stochastic Nash equilibrium problems (SNEPs), it is natural for players to be uncertain about their complex environments and have multi-dimensional unknown parameters in their m…