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THREE.js: minecraft in a weekend

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I have been enjoying exploring the ideas behind procedural worlds and in a previous post even showed a simple voxel renderer based in THREE.js which would load chunks when the camera got close enough to the edge. That was based on the great tutorial here which explains how to create a voxel-based mesh in THREE.js such that it doesn’t use all of the machine’s resources for the smallest of worlds. I found that to be an invaluable source of information and continually referenced back to that throughout the weekend. Looking back at my git logs for this project to be able to type this up, I have no intention of this post being a tutorial in itself, my progress was as follows: Walking around rather than observer view Sideways collision detection - not walking through the map Changing to a system where there was a sensible grass - sand - water height system Adding trees Another optimisation for terrain generation in addition to the afor...
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Placing and sizing cities in an infinite world

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In my first post on this topic, I introduced the idea of ontogenetic generation. In this post, I want to explore some of the ideas I have had for being able to produce cities in a procedural world. There are a few resources I have found online which discuss the generation of procedurally generated cities but I haven't seen anything which discusses how you might place them in an infinite procedurally generated world like Minecraft. In my research into producing cities in the context of civilisations, I spent a lot of time looking into the way that the settlements in Dwarf Fortress are produced.  I found it surprising how little information there is about how settlements arise in the game. All of the interviews seem to focus on the terrain generation which is comprehensive. The more I have read about the systems used in the game the more interested I have become. First idea When thinking over the topic of how one might generate integrated city structures in a manner that would allow...
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Picking apart Perlin noise from first Principles

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Although there are a lot of tutorials explaining the what and even the how of Perlin noise and the general class of algorithms; gradient noise, I have found none explaining the why behind the algorithm. Why does this algorithm work? In this post I aim to build up perlin noise from first principles, explaining why we add each element to the algorithm as we do. We will start by trying to make a surface, perhaps for a computer game world map. We are aiming for something that looks like a mountainous region. We don’t want to hand craft this landscape as we want it to go on forever, how can we procedurally generate this world? Given we want the surface to be random, we could start with that. However as you can see that doesn’t lead to the most pleasing of surfaces, in fact it wouldn’t be traversable in the game. Our problem is that there is no smoothness from one place to another. The lowest of points could be adjacent to the highest of points. What we want is for it to take som...
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