World Model Design

The Dreamer 4 world model predicts the next state, reward, and continuation flag conditioned on action history.

World Model Design

Core components:

• Temporal Transformer with 12–24 layers.

• Latent dimension: 512–1024 depending on compute.

• Uses categorical latents with 1% unimix for KL stability.

• Shortcut forcing aligns long-term rollouts with physical realism.

Training losses:

• Symlog reconstruction

• KL with free bits = 1 nat

• Reward prediction via two-hot bins

• Continuation prediction via logistic head