Dreamer V3 Reproduction

Key Insight

DreamerV3 learns a compact world model of the environment and then trains its policy almost entirely "in imagination" — rolling the policy forward inside the learned latent dynamics instead of the slow, expensive real environment. Its claim to fame is generality: a single fixed set of hyperparameters clears tasks as different as Atari games and collecting diamonds in Minecraft, which had long been an open problem in RL where each task usually needs its own tuning. Reproducing it on a custom environment is the best way to feel how much work the model-based world model does and how few knobs you actually have to touch.