Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing

Researchers propose Decision MetaMamba (DMM), a new AI model architecture that improves offline reinforcement learning by addressing information loss issues in Mamba-based models. The solution uses a dense layer-based sequence mixer and modified positional structure to achieve state-of-the-art performance with fewer parameters.