We propose a new, unsupervised, and adaptive Decision-Making framework called SIDM for Reinforcement Learning. This approach handles high complexity environments without manual intervention, and increases sample efficiency and policy effectiveness. site at https://ringbdstack.github.io/SIDM/ - View it on GitHub