We define this category as AI games in which agents are able to produce or consume natural language.
It dawned on Ciro Santilli that it would be very difficult to classify an agent as an AGI if tthat agent can't speak to take orders, read existing human generated documentation, explain what it is doing, or ask for clarification.
Video 1.
Human player test of DMLab-30 Select Described Object task by DeepMind (2018)
Source. This is one of the games from DeepMind Lab.
Video 2.
WorldGPT by Nhan Tran (2023)
. Source. Not the most amazing demo, but it is a start.
DeepMind Lab by Ciro Santilli 37 Updated 2025-07-16
TODO get one of the games running. Instructions: github.com/deepmind/lab/blob/master/docs/users/build.md. This may helpgithub.com/deepmind/lab/issues/242: "Complete installation script for Ubuntu 20.04".
It is interesting how much overlap some of those have with Ciro's 2D reinforcement learning games
The games are 3D, but most of them are purely flat, and the 3D is just a waste of resources.
Video 1.
Human player test of DMLab-30 Collect Good Objects task by DeepMind (2018)
Source.
Video 2.
Human player test of DMLab-30 Exploit Deferred Effects task by DeepMind (2018)
Source.
Video 3.
Human player test of DMLab-30 Select Described Object task by DeepMind (2018)
Source. Some of their games involve language instructions from the use to determine the desired task, cool concept.
Video 4.
Human player test of DMLab-30 Fixed Large Map task by DeepMind (2018)
Source. They also have some maps with more natural environments.
At twitter.com/togelius/status/1328404390114435072 called out on DeepMind Lab2D for not giving them credit on prior work!
This very much looks like like GVGAI which was first released in 2014, been used in dozens (maybe hundreds) of papers, and for which one of the original developers was Tom Schaul at DeepMind...
As seen from web.archive.org/web/20220331022932/http://gvgai.net/ though, DeepMind sponsored them at some point.
Or is real word data necessary, e.g. with robots?
Fundamental question related to Ciro's 2D reinforcement learning games.
Bibliography:
DeepMind by Ciro Santilli 37 Updated 2025-07-16
They seem to do some cool stuff.
They have also declined every one of Ciro Santilli's applications for software engineer jobs before any interview. Ciro always wondered what does it take to get an interview with them. Lilely a PhD? Oh well.
In the early days at least lots of gamedev experience was enough though: www.linkedin.com/in/charles-beattie-0695373/.
AlphaGo Zero by Ciro Santilli 37 Updated 2025-07-16
Figure 1.
AlphaGo Zero cheat sheet by David Foster (2017)
Source.
AlphaZero by Ciro Santilli 37 Updated 2025-07-16
www.quora.com/Which-chess-engine-would-be-stronger-Alpha-Zero-or-Stockfish-12/answer/Felix-Zaslavskiy explains that it beat Stockfish 8. But then Stockfish was developed further and would start to beat it. We know this because although AlphaZero was closed source, they released the trained artificial neural network, so it was possible to replay AlphaZero at its particular stage of training.
gvgai by Ciro Santilli 37 Updated 2025-07-16
The project kind of died circa 2020 it seems, a shame. Likely they funding ran out. The domain is dead as of 2023, last archive from 2022: web.archive.org/web/20220331022932/http://gvgai.net/. Marks as funded by DeepMind. Researchers really should use university/GitHub domain names!
Similar goals to Ciro's 2D reinforcement learning games, but they were focusing mostly on discrete games.
They have some source at: github.com/GAIGResearch/GVGAI TODO review
OpenAI by Ciro Santilli 37 Updated 2025-07-16
In 2019, OpenAI transitioned from non-profit to for-profit
so what's that point of "Open" in the name anymore??

Pinned article: Introduction to the OurBigBook Project

Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
We have two killer features:
  1. topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculus
    Articles of different users are sorted by upvote within each article page. This feature is a bit like:
    • a Wikipedia where each user can have their own version of each article
    • a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
    This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
    Figure 1.
    Screenshot of the "Derivative" topic page
    . View it live at: ourbigbook.com/go/topic/derivative
  2. local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:
    This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
    Figure 2.
    You can publish local OurBigBook lightweight markup files to either https://OurBigBook.com or as a static website
    .
    Figure 3.
    Visual Studio Code extension installation
    .
    Figure 4.
    Visual Studio Code extension tree navigation
    .
    Figure 5.
    Web editor
    . You can also edit articles on the Web editor without installing anything locally.
    Video 3.
    Edit locally and publish demo
    . Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.
    Video 4.
    OurBigBook Visual Studio Code extension editing and navigation demo
    . Source.
  3. https://raw.githubusercontent.com/ourbigbook/ourbigbook-media/master/feature/x/hilbert-space-arrow.png
  4. Infinitely deep tables of contents:
    Figure 6.
    Dynamic article tree with infinitely deep table of contents
    .
    Descendant pages can also show up as toplevel e.g.: ourbigbook.com/cirosantilli/chordate-subclade
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact