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An interactive environment where protozoa-like entities live, die, and have offspring whose behaviours and morphologies can change.
| Date | Stars |
|---|---|
| 2026-07-25 | 272 |
| 2026-07-28 | 272 |
| 2026-07-30 | 272 |
| 2026-08-06 | 272 |
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# Evolving-Protozoa Check the simulation out on YouTube: [](https://www.youtube.com/watch?v=fEDqdvKO5Y0) Come discuss the project on [discord](https://discord.com/invite/GY5UJxbBnq)! ## Overview The aim of this project is to create an environment where protozoa-like entities can evolve their behaviours and morphologies in order to survive and reproduce. The simulation takes place in a 2D environment with Newtonian physics implemented with Verlet integration. The following screenshot shows a zoomed-out view of the entire environment. In the screenshot below, can see procedurally generated rocks shown as brown-grey triangles that form rigid boundaries for cells moving around the tank fluids. The bright green cells are plants that serve as a sources of energy and mass for protozoa. These plants emit chemical pheromones that spread through the environment, and gradients of which can be detected by the protozoa. These pheromones are visualised in the screenshot and can be seen as the glowing green trails dispersed around and behind plant cells. ## Running the Simulation **Prerequisites:** Make sure you have [Java version 9 or greater](https://www.techspot.com/downloads/6463-java-se.html) installed. If you don't know how to install it, then hopefully [this tutorial](https://java.tutorials24x7.com/blog/how-to-install-java-16-on-windows) will help you out! Start by downloading the latest version from the [Releases page on GitHub](https://github.com/DylanCope/Evolving-Protozoa/releases). The program will be downloaded as a ZIP file, so unzip it and locate the `Evolving-Protozoa.jar` file. You should also see a `run.bat`, a `saves` folder, and a `config` folder. If you are on Windows, you can launch the simulation by double-clicking the `run.bat`, otherwise, you can manually run the jar file from the terminal using the command in the `run.bat`. You should be met with a launch screen where you can reload a previous save or start a new one. **Accessing Simulation Data:** The simulation records a lot of data as it runs, and makes back-ups of the tank at various stages. In the save's folder you can find CSV files containing the genomes of each protozoan, and overall statistics from the simulation polled at different moments in time. **Configuring the Simulation:** There are various parameters that can be changed by editing the `config/default_settings.yaml` file before creating a new simulation. For an existing save, you can change the parameters by editing the `settings.yaml` file in the folder corresponding to the save. These changes will not take effect until you close and reload the simulation. **Linux:** The project is developed and tested on Windows, but a user has created a [build of the software on the Arch Linux Repository](https://aur.archlinux.org/packages/evolving-protozoa). _Note:_ This is not maintained by the original developer. It may be out-of-date or untested. #### Controls Once you have the simulation running, there are a few controls that you might want to utilise. - F1: Toogle Pause - F10: Toggle rendering chemical grid - useful for increasing performance - F11: Toggle anti-aliasing - useful for increasing performance - F12: Toggle showing the UI **Using the REPL.** Another useful feature is the ability to interact with the simulation through the commandline REPL. You can access it through the terminal that launched the program, in IntelliJ this will be in the run tab. The REPL is a simple commandline interface, you can start by typing help to see the available commands.  The most useful command is the `toggleui` command, which completely closes the program window and runs the simulation headless at maximum speed. The `settime` and `gettime` commands will allow you to control the simulation time, i.e. the amount of time that the
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ef1152ed1ff838a7, topic:simulation