A small project showcasing genetic algorithms.
There are small creatures called "bups", and their goal is to reach the yellow circle. They can jump a limited amount of times, after which they will be evaluated based on their distance to the goal. They will then create a new generation of bups, using genes randomly (although better performing bups have a higher chance to be chosen). The original population is killed off (except for the best bup) and the process repeats.
The indicators on top show you the statistics. Fitness increases the closer a bup gets to the goal. As soon as a bup reaches the goal, its fitness is increased massively. However, the fitness can be increased even more by reaching the goal faster (this is the time indicator).
Note that not every simulation will reach the end. Sometimes the RNG is so bad that the genetic algorithm can't win. If fitness seems to be stuck after a couple hundred generations, refreshing might help. Don't forget that you can click anywhere to enable fastmode, this drastically speeds up the process. Click again to turn it off.
There are three color modes:
- random color (easier to distinguish between bups)
- color based on distance
- color based on amount of jumps left (default)
Feel free to pick the one you like at the bottom of the file bup.js.
It is possible to run this script in your browser. If you want to change the code however, download or clone the repo, and open index.html. Alternatively you can host a local server to run it on. It should work straight away. If not, please report the bug so I can do absolutely nothing whatsoever to fix it.
Feel free to report any bugs you encounter as an issue, however I can't promise to look at it. If you want to add a feature, go ahead and fork this repo. Most likely I won't accept any pull requests, although I'd be more than glad to link to your repo from this readme.