Welcome to the Self Driving Car Simulation! This simulation demonstrates how a car uses sensor data to detect obstacles and make decisions to navigate its environment.

In the context of self-driving cars using neural networks, "mutation" is a concept borrowed from genetic algorithms.

Genetic algorithms are a type of optimization algorithm that mimics the process of natural selection. They use techniques inspired by evolutionary biology such as mutation, crossover (reproduction), and selection (survival of the fittest).

In the case of self-driving cars, a neural network defines the behavior of the car, and its mutation and survival skills are decided using genetic algorithms. The "mutation" here refers to small, random modifications in the neural network's weights and biases. This introduces variability and helps the algorithm explore a wider range of possible solutions.