🧠 World Model Demo
Watch an AI agent "think" before it acts!
Unlike reactive AI that just responds to inputs, this agent uses a world model to:
- Imagine what would happen if it took each action
- Evaluate which imagined future is best
- Act based on its mental simulation
👉 Click "Think & Move" to watch the agent plan its path to the ⭐ goal!
🎮 Controls
Manual controls (to compare with agent):
| Aspect | Language Model (GPT, Claude) | World Model (This Demo) |
|---|---|---|
| Predicts | Next word in text | Next state given action |
| "Thinking" | Generates plausible text | Simulates physical outcomes |
| Planning | Implicit (chain-of-thought) | Explicit (tree search) |
The key insight: This agent can "imagine" taking actions and see the results before committing to them in the real world. It's like planning your route on a map before driving.
Real examples: MuZero (mastered Chess/Go without knowing rules), Dreamer (robot control), IRIS (Atari games)
World models are important for AI safety because:
- Predictability: We can inspect what futures the agent is considering
- Interpretability: The agent's "reasoning" is explicit, not hidden
- Control: We can verify the agent isn't planning harmful actions
- Corrigibility: Planning agents can incorporate "avoid irreversible actions"
Understanding how AI systems model the world helps us build systems we can trust.