Yuhu Cheng

Return-Critic: Bridging Goal Discrepancy for Efficient Visual Reinforcement Learning

Sample inefficiency remains a challenge in pixel-based visual reinforcement learning (RL), primarily due to ineffective state representation learning. While recent advances employ auxiliary tasks to improve representation learning, their representation goals (e.g., mask reconstruction, state predict…