5 papers
RetrDex: Efficient Object Retrieval in Cluttered Scenes with a Dexterous Hand
Fengshuo Bai, Yu Li, Jie Chu +5
Retrieving objects buried beneath clutter is both challenging and time-consuming, as complex support relationships make manipulation particularly difficult. Existing methods either…
Fusion-PSRO: Nash Policy Fusion for Policy Space Response Oracles
Jiesong Lian, Yucong Huang, Chengdong Ma +4
For solving zero-sum games involving non-transitivity, a useful approach is to maintain a policy population to approximate the Nash Equilibrium (NE). Previous studies have shown th…
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…
Conflux-PSRO: Effectively Leveraging Collective Advantages in Policy Space Response Oracles
Yucong Huang, Jiesong Lian, Mingzhi Wang +2
Policy Space Response Oracle (PSRO) with policy population construction has been demonstrated as an effective method for approximating Nash Equilibrium (NE) in zero-sum games. Exis…
Computing Ex Ante Equilibrium in Heterogeneous Zero-Sum Team Games
Naming Liu, Mingzhi Wang, Xihuai Wang +5
The ex ante equilibrium for two-team zero-sum games, where agents within each team collaborate to compete against the opposing team, is known to be the best a team can do for coord…