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With regards to Java vs C++, I've written a voxel engine in both (C++ version shown above). I've also been writing voxel engines since 2004 (when they were not vogue). :) I can say with little hesitation that C++ performance is far superior (but it is also more difficult to code). Its less about the computational speed, and more about memory management. ...
51
I'd suggest you start with 2D Perlin-noise. Something like this:
Then apply a threshold on the image, so that you get several isolated islands, as shown here:
I chose a threshold of 0.04, everything above the threshold would be colored blue. The rest remaining black. Then after that, it's time to determine which "islands" to keep and which to throw away.
...
50
I think this is good case for using either binary or ternary space partition.
On first pass, split house space into halls and {blocks of rooms}. Get next big chunk, split it into {hall and chunk} or {2 chunks and hall between them}. On every step, rotate slicing direction by 90 degrees. Stop when {no more big chunks left} or {total hall area reached limit}.
...
48
Here's a rough idea using image processing transformations to isolate the features of interest:
Apply a flood fill from an ocean cell to make a mask of all ocean cells. Depending on how your rivers are set up, you might need an extra elevation or clearance criterion to keep the ocean mask from flowing inland. ;)
Apply a local smoothing to the edge of this ...
45
From a pragmatic standpoint..
If someone isn't going to be playing your game over and over again, but instead is going to play through once from start to end using checkpoints or free saves (like in most non-roguelikes), then why would you spend your time on implementing procedural generation for your world, instead of just making a single, static, well-...
40
In the real world, those provincial borders will often be following geological features like rivers.
So maybe a good approach would be to model the geology of the island and have the borders fall out of this?
Red Blob Games has some good articles on this subject, with nice looking results.
His approach seems to involve using Voronoi tessellation, and ...
39
Amit Patel, a user of this site, has created a wonderful resource of information about random world generation that will certainly be of use to you.
Further there are some great questions/answers about procedural generation on this site.
Road / river generation on 2d grid map
Procedural world generation oriented on gameplay features
How can I generate ...
35
Back when I experimented with this type of thing (late 1990s), I read some papers and books to learn about water flow, but I didn't keep a record of which ones I looked at. I ended up doing my own thing because I wanted to handle erosion. I wanted rivers to produce canyons and floodplains. I wanted dam reservoirs to fill up with sediment. I wanted rivers to ...
33
One of the best, and most used, algorithms I've seen out there is generating dungeons using Binary Space Partitioning.
The best general explanation I've read is the one found in The Chronicles of Doryen (attached at the end for backup purposes) because explains the procedure without getting into the code, thus leaving the implementation to the reader.
Two ...
32
It looks like you're looking for "Turbulence", "Fractional Brownian Motion", or something similar.
This is where we take multiple samples of the noise at different scales - like the different panes in your first image - and add them together.
Each noise sample is commonly called an "octave". For each octave we add, we sample at a higher frequency (so the ...
31
To get something like this:
Create an icosahedron (20-sided regular solid) and subdivide the faces to get a sphere (see code below).
The idea is basically:
Create a regular n-hedron (a solid where every face is the same size and every edge is the same length). I use an icosahedron because it's the regular solid with the greatest number of faces. (There's ...
29
The way Dragons Abound identifies bays is to walk along the coastline and find two spots on the coastline where the straight-line distance between the spots is less than the distance along the coastline between the spots. This is the sinuosity of the coastline between the two spots. By selecting a sinuosity limit and limits for the straight-line distance ...
27
By way of analogy
A circuit does not generate power. A light bulb does not generate power. A battery does not generate power. None of the things which use or store generated power, are power generators.
A gasoline-driven generator is a power generator.
A solar panel setup is a power generator. They can be expected to spontaneously generate when they are ...
27
I would solve this problem with two passes of Voronoi diagrams:
First Pass: Region Partitioning
The first pass would use a somewhat sparse distribution of points (i.e. the distance between the points should be relatively large) in order to roughly divide the island into regions (see the note below regarding point generation). Next generate a Voronoi ...
26
To briefly answer your main question first, the main advantages of a procedurally generated game world are that:
The world can be huge, much larger than any manually designed game world could possibly be.
The world (or at least parts of it) can be regenerated for each game, potentially increasing replay value, since the player will always have something new ...
24
You can take advantage from the fact that your desired design lumps the rooms in rectangular rooms surrounded by corridors. With that in mind, I would do this:
Design the corridors and the "big spaces" for rooms
Fill in each "big space" with rooms
Filling up the big spaces with rooms can be done easily if you start with the rooms at the borders - they have ...
23
You could use perlin noise, which is normaly used for heightmap generation.
Perlin noise in games
Then you could use the heights as an adviser, how high the chance of grass/dirt occuring in one region of the map is.
Example (Perlin noise values from 0-256):
If the value is over 200 the chance that grass is placed is 80% (dirt 20%).
If the value is between ...
23
Use a slice of higher-order noise. If you used 2d noise for a height-map before, use 3D noise with the last coordinate fixed instead. Now you can slowly change the position in the last dimension to modify the terrain. Since Perlin noise is continuous in all dimensions, you'll get smooth transitions as long as you smoothly change the position where you sample ...
21
For the base land, make two 2D continuous noise fields (Perlin, Simplex, Wavelet, a combination thereof - whatever works for you), one with mostly low frequency. low amplitude parts for the upper limit of the land, the other with both high frequency, high amplitude parts and low frequency, high amplitude for the lower limit of the land. Where the lower limit ...
21
"Procedural" means that some algorithm made the content. This is opposed to content being created manually by a human.
"Dynamic" means that the content changes over time. This is opposed to "static" content that does not change after being created, or only changes in predefined ways e.g. key-framed character animation.
You can also have in-game player-...
21
A good place to start with procedural city generation is Parish and Müller's Procedural Modeling of Cities. Their paper presents an L-System in which rules concerning population density & road patterns (rectangular grid, radial & least elevation change) are combined and then fixed to accommodate local constraints such as water fronts & road ...
20
L-Systems, from what I can tell*, are a set of grammar-like substitution rules that you can apply recursively to get interesting, "organic" results.
Plants are where L-Systems are often used, as they show a lot of recursive growth (i.e. branch splits off into more branches). For a simple example, I'll show a "lollipop" tree generated using an L-System:
...
19
Cloud generation is fun! I'll cover both offline and runtime methods.
Pre-rendered clouds
If you want to pre-render your cloud textures offline, look no further than Photoshop (or Gimp, if you prefer). Both programs can easily generate cloud patterns. Menu items tend to move around between releases, but as of Gimp 2.8.2 the core command you're looking for ...
18
What you could do is randomly generate a Voronoi map like this:
Picking random center points (see the black dots) and randomly decide if they are grass or dirt.
Then for over all tiles, check if it's closest to a center point of dirt or a grass.
Done!
If what you did previously is "flip a coin" for each tile (noise), generating a Voronoi diagram will ...
18
It can also be very useful when your map generation algorithm is deterministic and repeatable based on an initial seed value. So when you enter the same seed value, you get the same map. This might be easier to implement than you think. Most random number generation APIs can be initialized with a seed value and then always generate the same sequence of ...
17
I can't give you a Unity-specific answer (sorry!), but I can tell how I would solve this. I would generate a bunch of points on a circle using the blue vector.
First, what is a circle? Well, a circle looks like this:
However, graphics hardware can't really draw perfect circles. You're always going to end up with a polygon approximation:
We do this ...
16
I travelled in a lot of "hot" countries in the 10 last years and each time I went to elevated areas it was cold or very cold even when I was close to the equator.
In fact elevated areas are semi-arid to arid. Vegetation is small (except some special species like cactus) and burned (by sun and cold). Most of the time, there is very little snow except at ...
16
While the existing answers provide a good way to achieve what the images in the question show, the comments revealed that the goal is to generate an image as shown below:
This type of noise is quite different from the noise shown in the images of the question, as it forms close isolated blobs.
Turns out that this kind of noise is called turbulence which (...
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