4 papers
DIDO: Distilling Interaction-Centric Dynamics into One-Step Denoising for World Action Models
Jing Lyu, Shuanghao Bai, Runze Xiao +11
World Action Models (WAMs) use video generation models to predict future visual dynamics for robotic manipulation, but iterative denoising introduces additional latency for closed-…
Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Games
Runyu Lu, Peng Zhang, Ruochuan Shi +5
Equilibrium learning in adversarial games is an important topic widely examined in the fields of game theory and reinforcement learning (RL). Pursuit-evasion game (PEG), as an impo…
ARAC: Adaptive Regularized Multi-Agent Soft Actor-Critic in Graph-Structured Adversarial Games
Ruochuan Shi, Runyu Lu, Yuanheng Zhu +1
In graph-structured multi-agent reinforcement learning (MARL) adversarial tasks such as pursuit and confrontation, agents must coordinate under highly dynamic interactions, where s…
R2PS: Worst-Case Robust Real-Time Pursuit Strategies under Partial Observability
Runyu Lu, Ruochuan Shi, Yuanheng Zhu +1
Computing worst-case robust strategies in pursuit-evasion games (PEGs) is time-consuming, especially when real-world factors like partial observability are considered. While import…