This project aims to create a simulation of artificial life using cellular automata and neural networks. The simulation will allow studying the effects of environmental factors on the evolution of cells and how different strategies for survival emerge.
To run this simulation, you will need to have Python 3 installed on your system. You will also need to install the following Python packages:
You can install these packages using pip by running the following command:
pip install --update pip
pip install arcade numpy matplotlib scipy
To run the simulation, you need to execute the main.py script:
python main.py
This will launch the simulation window, where you can observe the artificial life forms evolve.
The simulation uses a cellular automata model where cells are placed on a grid and interact with their neighbors based on predefined rules. Cells require energy to live and perform actions, and if they do not have enough energy, they die and are unable to reproduce.
- Light level
- Other cells (differentiating by species)
- Time of the simulation
- Current energy levels
- Moving in four directions
- Photosynthesizing
- Eating other cells
- Cloning themselves with some mutations
The simulation uses a neural network to tie observations to actions. The number of neural connections is limited to simulate biological systems.
The simulation uses natural selection. Cells with advantageous traits are more likely to survive and reproduce, passing on their traits to their offspring.
Our simulation showed that different strategies for survival emerge based on environmental factors. In all environments, cells that were able to photosynthesize were more likely to survive and reproduce. On the other hand, cells that were able to move quickly and consume other cells were more likely to be killed due to being eaten by its children.
We also observed that mutations played a significant role in the evolution of cells. Mutations that allowed cells to photosynthesize more efficiently or move more quickly were more likely to be passed on to offspring.
Furthermore, our simulation provided insights into the behavior of living organisms. We observed that cells were more likely to consume other cells of the same species rather than different species, indicating that there may be some level of recognition between cells of the same species.
This project is licensed under the MIT License. See the LICENSE file for more information.