This is an idea I've had from reading /r/SubredditSimulator, a subreddit where bots post content using Markov chains. I've been giving it some thinking and I thought I'd share it. I don't have yet anything to show for it as I'm unable to code at the moment, but might try it later. The idea is quite simple: let's use some sort of markov Chains to make our random maps nicer. The biggest problems in our random maps, in terms of niceness, is not so much the larger elements (such as continent shape, ...) but the finer details. It just looks too random quite often, compared to scenarios. My idea is simply to use markov chains to replicate those scenario achievements in random maps. I won't go into details on markov chains (google it), but basically the idea would be to analyze scenarios of a similar biome (or may only one map, if it's good enough. Fiddling with the data would be needed.), and then use this as a database in a "beautification" pass for random maps. So RM would still create the maps as we do know, put terrains as we do know, then add basic "necessary" entities, such as trees, player entities, and could also add some larger beautification elements. Then we'd go into a beautification pass. I see a few ways this could work: For each "important" entity, check what "decoration" entities are usually placed around (from the markov chains) and place those.For each terrain type, check which decoration entities can be found aroundPossibly this would require us to "pre-sort" important entities by checking how many important entities they have around (as you might place different stuff around a lone tree than in a forest), but this would have to be checked. It might be extended to actual terrains too, to make it easier to have nice transitions, but I'm not entirely sure it'd work so well. Just an idea, anyways.