WORLD MODEL · IMPLEMENTATION LAB

World Model Implementation Lab

Explore compact PyTorch reference implementations for the core mechanics of a world model: latent state, learned dynamics, action conditioning, imagined rollouts and planning.

Observation→ Encoder→ Latent State→ Dynamics→ Rollout→ Planning

Implementation Library

Repository file

These examples are intentionally compact. They are reference implementations for learning and experimentation, not production robot or autonomous-system controllers.

Recommended learning path

1 · Latent Dynamics→ 2 · Action Conditioning→ 3 · Rollouts→ 4 · Planning→ 5 · End-to-end Training

Start small. First verify one-step state prediction. Then test repeated rollouts. Add planning only after the learned dynamics are useful for the target environment.