FANS: A Flatness-Aware Network Structure for Generalization in Offline Reinforcement Learning
FANS is presented, a generalization-oriented structured network framework that promotes flatter and robust policy learning by guiding the optimization trajectory through modular architectural design and validate the effectiveness of FANS in mitigating overestimation and promoting generalization.