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Reviewed in POC · content version 3

Review World Model

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Definition

A world model is a representation — learned from experience or built by hand — that a system uses to predict how an environment may change and how its own actions may affect future states.
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Plain-Language Explanation

The model captures selected regularities about objects, actors, dynamics, or consequences so an AI system can simulate possibilities or plan beyond the immediate input.
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Why It Matters

Planning depends on the representation matching the relevant environment. Missing rules, changing conditions, or mistaken identity can produce confident but unsafe action.
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Example

A robot uses a learned representation of movement and object interaction to predict which route and action sequence is likely to reach a target safely.
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Common Misconception

A world model is not a complete or objective copy of the world and does not establish common sense or humanlike understanding.
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Remember It This Way

The system acts on its model of the world, not the world directly.
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Related Terms

* [[system|System]] * [[scenario|Scenario]] * [[context-to-reality-drift|Context-to-Reality Drift]] * [[ai-agent|AI Agent]] * [[objective-escape|Objective Escape]]
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Sources

* [Ha and Schmidhuber, *World Models*](https://arxiv.org/abs/1803.10122) — primary research on learning compressed spatial and temporal representations of environments for agent behavior.
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Learn More

* Check assumptions against reality with [[context-to-reality-drift|Context-to-Reality Drift]].
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