> Genetic Algorithm_

Evolution Simulation

[INFO] Genetic algorithms recreate Darwinian evolution on a computer. Mutation, crossover, natural selection — experience in seconds what life took 4 billion years to achieve.

[ STATUS ]

Generation:

Best Fitness:

0.0%

Avg Fitness:

0.0%

Reached:

0/100

[ Fitness History ]

--- Best Fitness- - Avg Fitness

[ CONTROLS ]

Speed: 1x

Mutation Rate: 5%

Population: 100

Obstacles:

[ What is a Genetic Algorithm? ]

Each dot has "DNA" — an array of velocity vectors for each step. Dots with good DNA get closer to the target.

After each generation, the fittest individuals are selected as "parents" to create offspring. This is natural selection.

Offspring DNA gets random mutations, exploring new behaviors. Too much mutation causes chaos; too little causes stagnation.