most citedFusion-PSRO: Nash Policy Fusion for Policy Space Response Oracles

2 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2025

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…

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…

cs.GT2024

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…

cs.GT2024

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…

cs.CL2024

Efficient Model-agnostic Alignment via Bayesian Persuasion

Fengshuo Bai, Mingzhi Wang, Zhaowei Zhang +4

With recent advancements in large language models (LLMs), alignment has emerged as an effective technique for keeping LLMs consensus with human intent. Current methods primarily in…

cs.LG2024

Efficient Preference-based Reinforcement Learning via Aligned Experience Estimation

Fengshuo Bai, Rui Zhao, Hongming Zhang +5

Preference-based reinforcement learning (PbRL) has shown impressive capabilities in training agents without reward engineering. However, a notable limitation of PbRL is its depende…

cs.GT2024★ 2 cited

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…

cs.GT2024

Leveraging Team Correlation for Approximating Equilibrium in Two-Team Zero-Sum Games

Naming Liu, Mingzhi Wang, Youzhi Zhang +3

Two-team zero-sum games are one of the most important paradigms in game theory. In this paper, we focus on finding an unexploitable equilibrium in large team games. An unexploitabl…