Machine Learning Zone: OpenAI competition takes on Sonic the Hedgehog

They won’t be going in blind — the risk of an AI breaking from the first is too high. But while researchers will have all the time in the world to design a training and learning mechanism based on a selection of Sonic levels, the test will involve applying that training mechanism to a new set of levels, under a strict time limit (18 hours of game time).

This means you have to create an agent that understands not just one level of Sonic, but Sonic as a gestalt. If your AI knows all the shortcuts in Green Valley Zone, it may excel there, but when sent to the Chemical Zone, it’ll choke (like me) when it encounters the scary underwater parts.

You don’t jump like normal! It’s a lot of pressure with the stuff coming up!

It also means your algorithm has to train efficiently, which may involve all kinds of techniques and shortcuts. Minimizing training time means minimizing lazy learning and paying attention to multiple sources of information at once.

There are also different control methods, gimmicks and physics in each game, so it may be that identifying those before making the run could be critical to success. Really, there are all kinds of things to consider. (It’s making me want to go back and play these great games.)

Contestants will be using OpenAI’s Gym Retro platform, which essentially wraps an emulator playing Sonic (and a set of other Sega games) in the tools developers need to extract data, map inputs and so on.

Winners don’t get any cash or anything, but first through third place will get trophies and will have the opportunity to co-author a report on the contest. OpenAI’s reports are interesting and widely read, so it sounds like a good opportunity if you have the time and inclination — although, of course, “it’s great exposure” is the classic payment avoidance strategy.

There are lots more games in the package of games OpenAI is using — I’d like to see an AI take on Gunstar Heroes, or Golden Axe III.