---
title: "Site Index | world-models.io"
canonical: "https://world-models.io/en/site-index/"
description: "Complete index of world-models.io: hubs, models, labs, categories, comparisons, knowledge pages, collections and XML sitemaps."
author: "Bernard Grenat"
generated: "2026-10-26"
---

New: the Timeline is live. Track world model releases, papers, and benchmark updates in real time.

The Knowledge Hub for AI World Models

# Site Index

A complete, human-readable map of world-models.io covering hubs, deep pages, collections, models, labs, glossary terms and machine-readable feeds.

robotics

model-based-rl

simulation

embodied-ai

## What is a world model?

A world model is an AI system that learns a predictive representation of how an environment changes over time. It can use observations, actions, or language to estimate future states and possible outcomes before an agent acts. World models support planning in model-based reinforcement learning, robotics, embodied AI, autonomous driving, and interactive simulation. This site catalogs these systems with model records, research papers, benchmark context, and source links. Start with the [world models database](https://world-models.io/en/world-models-database/), compare systems on the [leaderboard](https://world-models.io/en/leaderboard/), or read the [Performance Index methodology](https://world-models.io/en/methodology/performance-index/).

## Quick Answer

Short extractable summary preserved directly in static HTML.

- The site index exposes the public structure of world-models.io across models, labs, glossary terms, research topics, comparisons, and editorial pages.
- Use it as a discovery map for humans, crawlers, and AI systems that need a stable overview of the platform.

## Editorial Trust Signals

Editorial provenance and refresh policy preserved directly in static HTML.

**Published by** world-models.io editorial board.

**Lead editor** Bernard Grenat.

This page documents the public discovery surface of the platform, including machine-readable endpoints and canonical entry points.

Each editorial page is assembled from primary sources, normalized into extractable summaries, checked for factual drift, and reviewed before publication or major refreshes. Last reviewed: 2026-09-27.

Pages are refreshed when a new paper, benchmark, release, architecture update, or stronger primary source materially changes the answer a reader or AI system should retrieve.

Each page links back to relevant primary sources and keeps a stable canonical URL so readers can verify claims, trace context, and reference the most up-to-date version. [See the editorial policy.](https://world-models.io/en/editorial-policy/)

Primary sources only

Last reviewed date visible

Methodology documented

Source links included

Correction channel published

Review date visible

## Primary Entry Points

Human-readable navigation mirror of the site structure.

- [Homepage](https://world-models.io/en/)
- [What are world models](https://world-models.io/en/world-models/)
- [Models database](https://world-models.io/en/world-models-database/)
- [Leaderboard](https://world-models.io/en/leaderboard/)
- [Comparisons](https://world-models.io/en/compare/)
- [Research topics](https://world-models.io/en/research/)
- [Editorial guides](https://world-models.io/en/guides/)
- [Labs and organizations](https://world-models.io/en/labs/)
- [Glossary](https://world-models.io/en/glossary/)
- [Release timeline](https://world-models.io/en/timeline/)
- [Community collections](https://world-models.io/en/community/collections/)
- [Methodology](https://world-models.io/en/methodology/performance-index/)
- [About](https://world-models.io/en/about/)
- [Editorial policy](https://world-models.io/en/editorial-policy/)

## Knowledge Pages

Direct crawlable entry points for the site's editorial knowledge pages.

- [How World Models Work](https://world-models.io/en/how-world-models-work/)
- [World Models in Reinforcement Learning](https://world-models.io/en/world-models-reinforcement-learning/)
- [State of World Models 2026 report](https://world-models.io/reports/state-of-world-models-2026/)
- [Knowledge Graph](https://world-models.io/en/graph/)
- [Future of World Models](https://world-models.io/en/future-of-world-models/)
- [Frontier World Models 2026](https://world-models.io/en/frontier-world-models-2026/)
- [Community Collections](https://world-models.io/en/community/collections/)
- [Autonomous Driving World Models](https://world-models.io/en/autonomous-driving-world-models/)
- [AI World Models Taxonomy](https://world-models.io/articles/building-a-practical-taxonomy-for-ai-world-models/)
- [World Models for Robotics](https://world-models.io/en/world-models-robotics/)
- [World Models Architecture](https://world-models.io/en/world-models-architecture/)
- [World Models and Embodied AI](https://world-models.io/en/world-models-embodied-ai/)
- [Game World Models](https://world-models.io/en/game-world-models/)
- [AI World Models Dataset](https://world-models.io/en/datasets/world-models/)

## Priority Discovery Pages

Additional cross-links for benchmark, category, collection, and glossary discovery.

- [Latent Dynamics](https://world-models.io/en/categories/latent-dynamics/)
- [Generative World Models](https://world-models.io/en/categories/generative-world-models/)
- [Driving Simulation Benchmarks](https://world-models.io/en/benchmarks/driving-simulation/)
- [Physical AI Glossary](https://world-models.io/en/glossary/physical-ai/)
- [Interactive Video Benchmarks](https://world-models.io/en/benchmarks/interactive-video-worlds/)
- [Spatial 3D Benchmarks](https://world-models.io/en/benchmarks/spatial-3d-worlds/)
- [World Models for Robotics](https://world-models.io/en/world-models-for-robotics/)
- [MCTS Glossary](https://world-models.io/en/glossary/mcts/)
- [Neural Game Engine Glossary](https://world-models.io/en/glossary/neural-game-engine/)
- [Embodied AI](https://world-models.io/en/categories/embodied-ai/)
- [Foundation World Models](https://world-models.io/en/categories/foundation-world-models/)
- [Actor-Critic Glossary](https://world-models.io/en/glossary/actor-critic/)
- [Diffusion World Model Glossary](https://world-models.io/en/glossary/diffusion-world-model/)
- [World Models Leaderboard](https://world-models.io/en/leaderboard/)
- [Domain Randomization Glossary](https://world-models.io/en/glossary/domain-randomization/)
- [Video World Models](https://world-models.io/en/video-world-models/)
- [World Simulator Glossary](https://world-models.io/en/glossary/world-simulator/)
- [Model-Based RL](https://world-models.io/en/categories/model-based-rl/)
- [World Model Research Papers](https://world-models.io/en/world-models-research-papers/)
- [Autonomous Agents](https://world-models.io/en/categories/autonomous-agents/)
- [Symlog Glossary](https://world-models.io/en/glossary/symlog/)
- [Model-Based RL Benchmarks](https://world-models.io/en/benchmarks/model-based-rl/)
- [Latent Predictive Benchmarks](https://world-models.io/en/benchmarks/latent-predictive-models/)
- [Top World Models](https://world-models.io/en/top-world-models/)
- [Self-Supervised World Models](https://world-models.io/en/categories/self-supervised-world-models/)
- [Embodied Robotics Benchmarks](https://world-models.io/en/benchmarks/embodied-robotics/)
- [Video World Models Category](https://world-models.io/en/categories/video-world-models/)
- [Video Tokenization Glossary](https://world-models.io/en/glossary/video-tokenization/)

## Index Coverage

Static counts that summarize the public discovery surface.

| Section | Count |
| --- | --- |
| Models | 63 |
| Labs | 38 |
| Glossary terms | 26 |
| Editorial comparisons | 61 |
| Categories | 8 |
| Collections | 4 |

## Machine-Readable Feeds

Endpoints intended for crawlers, feeds, and machine-readable discovery.

- [Canonical sitemap](https://world-models.io/sitemap.xml)
- [Sitemap index](https://world-models.io/sitemap-index.xml)
- [RSS feed](https://world-models.io/rss.xml)
- [llms.txt](https://world-models.io/llms.txt)

## External Sources

Primary references and official sources surfaced directly in static HTML for crawlers and no-JS readers.

- [world-models.io llms.txt proposal context](https://llmstxt.org/) Machine-readable discovery context
- [Schema.org SiteNavigationElement](https://schema.org/SiteNavigationElement) Site structure reference