I'm skeptical that machine learning has much to offer the typical roguelike developer. Most roguelikes approach a player/developer ratio of zero. For every suc

I'm skeptical that machine learning has much to offer the typical roguelike developer. Most roguelikes approach a player/developer ratio of zero. For every successful shipped roguelike with actual players, there are probably a thousand hobby roguelikes with no users but a happy developer or two wiling their time away. This is not a particularly lucrative corner of the gamedev world, so most are in it for the intrinsic motivation. Handcrafting a level generator is a lot of fun. Training an ML model might be fun too, but it seems like a very different sort of activity, and not necessarily one that appeals to roguelike devs. > so long as an appropriate loss function can be crafted (in practice this isn't very hard and proxies can even be used in tricky cases). I'm skeptical that this is as easy as you suggest. Everyone thinks making something "fun" is easy until they sit down to try. Fun is the knife-edge between familiarity and surprise. Optimizing for it is probably in the same order of difficulty as predicting the stock market: If you train your generator to be particularly fun in a certain way, players will quickly grow tired of it, which isn't fun.