Dual Advantage-Guided Offline Reinforcement Learning
Offline reinforcement learning aims to learn effective policies from fixed datasets without online interaction, necessitating conservative constraints to mitigate the out-ofdistribution issue. Although existing approaches alleviate this issue through conservative constraints or policy regularization, they still struggl...