1 citations · 1 across the 12 of their papers we have counts for
13 papers
The Price of Covertness: Dual-Control Navigation in Uncertain Flows under Adversarial Sensing
Ruimeng Hu, Botao Jin, Xu Yang
Covert navigation in an uncertain flow couples motion planning with information acquisition. A vehicle must estimate the local flow to navigate, while estimation error induces corr…
Strategic Inference of Adversarial Navigation Objectives for Unmanned Underwater Vehicles
Ruimeng Hu, Xu Yang
We study destination inference for adversarial unmanned underwater navigation in a spatially varying current field. The red vehicle is modeled as approximately following a Hamilton…
Optimal Design of Stealthy Attacks in Partially Observed Linear Systems: A Likelihood-Based Approach
Haosheng Zhou, Ruimeng Hu
We study the optimal design of stealthy attacks against partially observed linear control systems. We first propose a novel likelihood-based detection mechanism derived from the in…
Deception in Linear-Quadratic Control
Yerin Kim, Haosheng Zhou, Alexander Benvenuti +2
Systems operating in adversarial environments may inadvertently leak sensitive information to adversaries. To address this challenge, we revisit the linear-quadratic control framew…
Information Revelation and Alignment Faking in Stochastic Differential Games
Daniel Ralston, Xu Yang, Ruimeng Hu
In competitive games with private objectives, actions can reveal information about hidden parameters. However, quantifying such information revelation is nontrivial, since it depen…
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…
Finite-Agent Stochastic Differential Games on Large Graphs: I. The Linear-Quadratic Case
Ruimeng Hu, Jihao Long, Haosheng Zhou
In this paper, we study finite-agent linear-quadratic games on graphs. Specifically, we propose a comprehensive framework that extends the existing literature by incorporating hete…
A Deep Learning Analysis of Climate Change, Innovation, and Uncertainty
Michael Barnett, William Brock, Lars Peter Hansen +2
We study the implications of model uncertainty in a climate-economics framework with three types of capital: "dirty" capital that produces carbon emissions when used for production…