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math.OC2026

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…

math.OC2026

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…

math.OC2026

An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows

Liya Guo, Ruimeng Hu, Xu Yang +1

Continuous-time stochastic control with time-inhomogeneous jump-diffusion dynamics is central in finance and economics, but computing optimal policies is difficult under explicit t…

math.OC2025

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…

math.OC2025

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…

math.OC2025

Multi-Agent Relative Investment Games in a Jump Diffusion Market with Deep Reinforcement Learning Algorithm

Liwei Lu, Ruimeng Hu, Xu Yang +1

This paper focuses on multi-agent stochastic differential games for jump-diffusion systems. On one hand, we study the multi-agent game for optimal investment in a jump-diffusion ma…