1 citations · 1 across the 12 of their papers we have counts for
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Learning Mean-Field Games through Mean-Field Actor-Critic Flow
Mo Zhou, Haosheng Zhou, Ruimeng Hu
We propose the Mean-Field Actor-Critic (MFAC) flow, a continuous-time learning dynamics for solving mean-field games (MFGs), combining techniques from reinforcement learning and op…
Strategic Inference in Stackelberg Games: Optimal Control for Revealing Adversary Intent
Ruimeng Hu, Daniel Ralston, Xu Yang +1
We study a continuous-time stochastic Stackelberg game in which a leader seeks to accomplish a primary objective while inferring a hidden parameter of a rational follower. The foll…
Well-posedness of the relaxed Electron MHD equations with random diffusion
Ruimeng Hu, Qirui Peng, Xu Yang
We investigate a three-dimensional active-vector relaxation of the electron magnetohydrodynamics (EMHD) equations without resistivity. The relaxation replaces the electron current…
Finite-Agent Stochastic Differential Games on Large Graphs: II. Graph-Based Architectures
Ruimeng Hu, Jihao Long, Haosheng Zhou
We propose a novel neural network architecture, called Non-Trainable Modification (NTM), for computing Nash equilibria in stochastic differential games (SDGs) on graphs. These game…
Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach
Haosheng Zhou, Daniel Ralston, Xu Yang +1
Adversarial decision-making in partially observable multi-agent systems requires sophisticated strategies for both deception and counter-deception. This paper presents a sequential…
Integrating Sequential Hypothesis Testing into Adversarial Games: A Sun Zi-Inspired Framework
Haosheng Zhou, Daniel Ralston, Xu Yang +1
This paper investigates the interplay between sequential hypothesis testing (SHT) and adversarial decision-making in partially observable games, focusing on the deceptive strategie…