Long answer: trying to make it much easier to do simulation-based research using OpenTTD, and for any results found to be as reproducible as possible. There have been a few papers/dissertations that use OpenTTD, but it's tricky to do exactly what the authors did, or even in a few cases I suspect it was hard for them to repeat their own experiments or extract results from them. OpenTTDLab seeks to make these easier.
And, such research seems to often (/always?) use AIs, so that's the focus.
I also would like to be able to train an AI in some automated(/formal?) way, and maybe use OpenTTD to investigate something a bit more... supply-chain-y, but that's a work in progress (I've not even written an AI yet!)
But also a bit of a less formal "just run an AI/some AIs over some seeds and see" is also very much a use case. Am trying to strike that balance between something quite... exploratory, but still reproducible.
I thought it was time I got off my... and starting making an AI (https://github.com/michalc/SupplyChainLabAI - but it does nothing but log a debug message repeatedly at this point, I feel I have a long journey...)
But it makes me realise there is another use case for OpenTTDLab that I don't think I considered: regression tests for OpenTTD AIs?
Long answer: trying to make it much easier to do simulation-based research using OpenTTD, and for any results found to be as reproducible as possible. There have been a few papers/dissertations that use OpenTTD, but it's tricky to do exactly what the authors did, or even in a few cases I suspect it was hard for them to repeat their own experiments or extract results from them. OpenTTDLab seeks to make these easier.
And, such research seems to often (/always?) use AIs, so that's the focus.
I also would like to be able to train an AI in some automated(/formal?) way, and maybe use OpenTTD to investigate something a bit more... supply-chain-y, but that's a work in progress (I've not even written an AI yet!)
But also a bit of a less formal "just run an AI/some AIs over some seeds and see" is also very much a use case. Am trying to strike that balance between something quite... exploratory, but still reproducible.