[Eridrus]

> - I highly recommend supporting an identical interface found in OpenAI's gym. Check their docs out. Even better would be to have your game importable as an environment in gym.

> - Configurable screen resolution would be great (eg. output 120x100)

I think both of these things assume you are going to be doing RL from pixels. I think to support a wider variety of RL/control research, you should be able to get the game state in a structured form and not just a flat vector the way gym does it.

But even then, that's still just one branch of AI research. I've seen people optimize how games behave to optimize engagement with the game, and in that setting just controlling the player is not enough. The work I saw looked at controlling level progression to increase engagement, but you could imagine controlling other bits of the game, particularly relevant if your game is not symmetric and the metric you care about is not just making the best AI.

Maybe not AI, but people also do research on how to replace components of games with ML components and the results can be pretty cool, e.g. https://www.youtube.com/watch?v=Ul0Gilv5wvY

Which is just to say that there is not one size fits all approach here.