Chenjia Bai

SelfBC: Self Behavior Cloning for Offline Reinforcement Learning

2024 · arXiv (Cornell University)

Policy constraint methods in offline reinforcement learning employ additional regularization techniques to constrain the discrepancy between the learned policy and the offline dataset. However, these methods tend to result in overly conservative policies that resemble …

Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective

2025

World models have recently attracted growing interest in Multi-Agent Reinforcement Learning (MARL) due to their ability to improve sample efficiency for policy learning. However, accurately modeling environments in MARL is challenging due to the exponentially …