DeepMind Lab2D

I've taken a look at the API for Lab2D and it's very abstract. What you have to work with are functions for strings, integers and floating point numbers glued together with callback functions and a bare-bones engine for running all of it through the equivelent of a game loop. In effect you have to define the meaning behind all those numbers and callback functions to create your own simulation. There are no pre-defined humans, robots, vehicles, generators, conveyer belts, minerals, etc for you to interact with.

It's all very hardcore and suitable for numerical academic research, but IMHO not very accessible to a what I think is a fairly large audience which wants a ready made world in which to play with some AI agents. At least I assume that such an audience exists based on the many posts here mentioning personal AI projects.

What I think is needed the equivelent of a game engine with an API allowing you to plug in AI models in place of the entities within it. Something similar to world games like Factorio, Rimworld, Hearts of Iron, Anno 1800, but with an API allowing you to create and control in-world assets. Something similar to the StarCraft API used by AlphaStar.

I think we really need a standardized world sim as a server, equipped with some gRPC API to control its entities and get out information. You run your world sim on some machine or Kube cluster and interact with it via a well known API. Plug in whatever AI you need into the API spawn a couple million agents on a couple million tile world and off you go. I suspect you could do a very fast sim with modern multi-core desktop CPUs.

Hmm, I am looking for an interesting project...

It would be cool to have a UI like this.

https://otoro.net/slimevolley/

Nice! Looks like it even does level generation. I’ll have to give this a closer look.

I made a medium-popular scripting language/game-engine ( https://www.puzzlescript.net/ ) whose games are by chance in the domain of this framework. I wonder if it’d be worth it to try write a wrapper for it...

It seems like creating an API for your agent to train with can be as difficult an engineering problem as the machine learning itself.