--- title: "AMI vs Ha World Model | Cognitive World Models | world-models.io" canonical: "https://world-models.io/en/compare/ami-vs-ha-world-model/" description: "From Ha's dream-based learning to AMI's autonomous intelligence: comparing two cognitive approaches to world models." author: "Bernard Grenat" generated: "2026-10-23" --- New: the Timeline is live. Track world model releases, papers, and benchmark updates in real time. The Knowledge Hub for AI World Models # AMI vs Ha World Model Two pioneering cognitive-inspired world models: Ha's 2018 World Model introduced the VAE+RNN+Controller architecture, while AMI proposes an autonomous machine intelligence framework inspired by biological cognition. 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/). ## Comparison Overview Main comparison summary preserved directly in static HTML. Two pioneering cognitive-inspired world models: Ha's 2018 World Model introduced the VAE+RNN+Controller architecture, while AMI proposes an autonomous machine intelligence framework inspired by biological cognition. ## Verdict Primary editorial conclusion preserved for non-JS crawlers and readers. Ha's World Model is a landmark: the first to demonstrate that an agent could learn a policy entirely inside a learned dream. AMI extends this vision toward full autonomous intelligence, proposing a modular architecture inspired by neuroscience. Ha's model is proven and foundational; AMI is a visionary framework pointing toward AGI-like world understanding. ## Key Differences Extractable difference list generated from the comparison table. - **Inspiration:** AMI - Biological autonomous intelligence; Ha World Model - Human mental simulation / dreaming. - **Architecture:** AMI - Modular cognitive architecture; Ha World Model - VAE + MDN-RNN + Controller. - **Training:** AMI - Self-supervised + intrinsic motivation; Ha World Model - Unsupervised feature learning + evolution. - **Domain:** AMI - General cognitive tasks; Ha World Model - VizDoom, car racing. - **Key Contribution:** AMI - Framework for autonomous machine intelligence; Ha World Model - Proved agents can learn entirely in imagination. ## When To Use Each Static decision guidance for no-JS readers. ### Choose AMI when... Choose AMI when its documented capabilities match your research or deployment requirements. ### Choose Ha World Model when... Choose Ha World Model when its documented capabilities match your research or deployment requirements. ## Comparison Table Ha's World Model is a landmark: the first to demonstrate that an agent could learn a policy entirely inside a learned dream. AMI extends this vision toward full autonomous intelligence, proposing a modular architecture inspired by neuroscience. Ha's model is proven and foundational; AMI is a visionary framework pointing toward AGI-like world understanding. | Dimension | AMI | Ha World Model | | --- | --- | --- | | Inspiration | Biological autonomous intelligence | Human mental simulation / dreaming | | Architecture | Modular cognitive architecture | VAE + MDN-RNN + Controller | | Training | Self-supervised + intrinsic motivation | Unsupervised feature learning + evolution | | Domain | General cognitive tasks | VizDoom, car racing | | Key Contribution | Framework for autonomous machine intelligence | Proved agents can learn entirely in imagination | | Year | 2024 | 2018 | ## Performance Index Snapshot High-level scoring context for the models referenced in this comparison. | Model | Category | Index v1.1 | Confidence | | --- | --- | --- | --- | | AMI World Model | Foundation World Model | N/A | N/A | | World Models (Ha & Schmidhuber) | Model-Based RL | 48/100 | high | | DreamerV3 | Model-Based RL | 88/100 | high | | V-JEPA | Self-Supervised World Model | 70/100 | medium | ## Frequently Asked Questions FAQ answers rendered directly into static HTML for extractable responses. ### Is AMI a successor to Ha's World Model? Not directly. AMI is a broader cognitive architecture proposal, while Ha's model is a specific implementable system. They share the insight that internal world simulation is key to intelligence. ## Quick Answer Short extractable summary preserved directly in static HTML. - AMI vs Ha World Model: this page compares where each system is stronger instead of forcing a universal winner. - Use the verdict for the short answer, then validate the trade-offs in the table, evidence sources, and benchmark context. - Related models and source links help connect this comparison to the broader world models landscape. ## 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 comparison page publishes a direct answer, explicit trade-offs, and source-backed evidence that can be validated against primary materials. 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 ## External Sources Primary papers and official sources for the models discussed on this comparison page. - [World Models (Ha & Schmidhuber) paper](https://arxiv.org/abs/1803.10122) Google Brain / IDSIA primary research source - [World Models (Ha & Schmidhuber) official page](https://worldmodels.github.io) Google Brain / IDSIA official page - [DreamerV3 paper](https://arxiv.org/abs/2301.04104) Google DeepMind primary research source - [V-JEPA paper](https://arxiv.org/abs/2404.08471) Meta primary research source