DIAMOND (DIffusion As a Model Of eNvironment Dreams) trains a reinforcement learning agent to act within an imagined environment generated by a diffusion model. The world model learns to predict future frames from current observations and actions, enabling the agent to plan and learn via simulated experience rather than real environment interactions. The project provides pretrained Atari and CSGO world models along with training code for both the diffusion model and the RL policy.