RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization

In safety-critical domains where online data collection is infeasible, offline reinforcement learning (RL) is attractive only if policies achieve high returns without catastrophic lower-tail risk. Prior work on risk-averse offline RL achieves safety at the cost of either (i) value/model-based pessim