3 papers
cs.CY2025
Social World Model-Augmented Mechanism Design Policy Learning
Xiaoyuan Zhang, Yizhe Huang, Chengdong Ma +6
Designing adaptive mechanisms to align individual and collective interests remains a central challenge in artificial social intelligence. Existing methods often struggle with model…
cs.LG2025
VLP: Vision-Language Preference Learning for Embodied Manipulation
Runze Liu, Chenjia Bai, Jiafei Lyu +3
Reward engineering is one of the key challenges in Reinforcement Learning (RL). Preference-based RL effectively addresses this issue by learning from human feedback. However, it is…
cs.LG2024
RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors
Fengshuo Bai, Runze Liu, Yali Du +2
Evaluating deep reinforcement learning (DRL) agents against targeted behavior attacks is critical for assessing their robustness. These attacks aim to manipulate the victim into sp…