This project contains a visual Ecosystem Simulator contaning elements from three levels of a food chain.
The program aims to simulate the basic life processes (movement, eating, reproduction, death) of the creatures
in as natural way as possible without complicating the program too much. The main focus of the program is to
implement Neural Networks using a state of the art genetic algorithm.
The simulation contains grass as the bottom most element of the food chain, which keeps spawning at random locations.
There are two more levels of the food chain which is constituted by rabbits and foxes. At the beginning of the simulation,
an initial quantity of all the elements spawn at random locations, the animals in which are then moving randomly within
the map area. Every animal is an instance of either the Fox or Rabbit class, which inherit from the parent class
Organism. There are several attributes which are speciied within the classes, where most of the attributes have a specific
range from which during the creation of an instance a random value is assigned to maintain diversity.
Within the assigned life span of the animals, they need to eat to survive. The rabbits need to find grass to survive and the foxes need to eat rabbit to survive. The animals have a hunger limit in days, before which they would require to eat again to survive. The gender of the animals are assigned randomly during their birth and the animals try to find a mate of the opposite gender to reproduce. After completion of the gestation period, new off-springs are born which inherit attributes from both the parents having equal probabilities of inheriting from either of the parent and a 10% (can be changed in the code) chance of mutation.