Experimentation on Genetic Algorithm to simulate an ecosystem adapting to its environment.
I was interested in building an Evolutionary Algorithm on my own for training purpose and chose a life simulation reacting to the environment conditions (temperature, humidity, etc. even though only temperature is implemented at the moment). The simulation doesn't stop on a success criteria but loop endlessly as the conditions are changing at the same time.
After the algo part, I built a front end to test it by controling the configuration and conditions, and visualise the population. For simplicity the algo runs in the browser. Changing the configuration and conditions doesn't reset the simulation.
At the moment, only the temperature is taken into consideration. Blue individuals have a temperature sensitivity below 18 degree Celsius. Green individuals have a temperature sensitivity between 18 and 25 degree Celsius. Red individuals have a temperature sensitivity above 25 degree Celsius.
As the simulation runs, the individuals' sensitivity evolves towards the actual conditions changing the individual colour. This is ensured by the selection, crossover and mutation parts of the algorithm.
The population stabilized at 15 degree Celsius
The population stabilized at 21 degree Celsius
The population stabilized at 28 degree Celsius
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