The Binding of Isaac, and its remake, Binding Of Isaac: Rebirth are one of my favourite games of all time. It’s a roguelite twin stick shooter, much like Enter the Gungeon.
It’s time for another in my series on how games do level generation. Let’s take a look at SLIGE, a random level generator for Doom. The original Doom. That’s right, we’re going back to the early 90s for this one.
Doom was one of the first games designed from the ground up to friendly to modding, and consequently the community around it exploded. In the years following its release, level packs and tools started to circulate for free. It was only a matter of time until someone designed a random level generator.
SLIGE was one of the first. It quickly became infamous because newcomers would often attempt to pass off the level it creates as their own. But they’d inevitably get caught – SLIGE levels have a very distinctive feel, as you can see in the video below.
SLIGE may not be the most sophisticated level generator out there, but its fame caught my eye. It was under development by author David Chess for a number of years, and so has lots to explore. In this article, we’ll delve into how exactly it works.
Since developing DeBroglie and Tessera, I’ve had a lot of requests to explain what it is, how it works. The generation can often seem quite magical, but actually the rules underlying it are quite simple.
So, what is the Wave Function Collapse algorithm (WFC)? Well, it’s an algorithm developed by Maxim Gumin for generating tile based images based off simple configuration or sample images. If you’ve come here hoping to learn about quantum physics, you are going to be disappointed.
WFC is explained briefly in Maxim’s README, but I felt it needed a fuller explanation from first principals. It is a slight twist on a much more broad concept – constraint programming. So much of this article is going to explain constraint programming, and we’ll get back to WFC at the end.
WFC is a very flexible algorithm, particularly with the enhancements I’ve designed, but at the same time, I’ve found it’s quite hard to actually get it to produce practical levels useful for computer games. The key difficulty is WFC doesn’t have any global structure to it, all it does it make the output generation look like the input locally, i.e. when viewing small rectangles of output at a time.
In this article, I share what I’ve learned to take your constraint based generators to the next level.
I’ve been playing a lot of Enter The Gungeon recently. It’s a great, brutally hard, twin stick bullet hell that reminded me a lot of Binding of Isaac. But as I’ve been playing it more and more, I realized that the dungeon design actually shows some subtle genius.
There are many procedural generators out there that produce sensible level layouts that manage pacing and rewards correctly, and there are other generators out there that provide levels that include loops and compact layouts. But it’s hard to find both in a single game. Really, the only other game I’ve heard attempting this is Unexplored.
So, naturally, I broke out the decompiler to reveal all of Gungeon‘s secrets to me. I’ll share with you what I found.
Diablo 1 is a classic 1996 hack and slash action RPG. It was one of the first popular attempts at bringing roguelikes to the masses, from the niche ascii art. It’s spun a host of sequels, and imitators. It’s known for a dark, moody atmosphere that intensifies as the player descends into the dungeon beneath the town of Tristram. It was one of the first games I played with procedurally generated maps, and it blew me away that generating such convincing areas was even possible.
I recently discovered that thanks to the discovery of various debug symbol files accidentally left lying around, several fans took it upon themselves to reverse-engineer the source code and clean it up into a good guess at what the original game is like. Thus began a week long deep dive into how exactly did lead developer, David Brevik, actually craft these levels. It may have taken away some of the magic of the game, but I learnt lots of techniques I think are applicable to anyone developing a similar game, which I share with you below.