Neural Networks | Car Race

import java.util.Collections;

float MUTATION_CHANCE = 0.3;
float MUTATION_MIN = 0.5;
float MUTATION_MAX = 0.7;

int BRAIN_SIZE = 100;
int CAR_SPEED = 5;

int END_X = 250, END_Y = 0;

void setup()
{
  size(500, 500);
  background(0);
}

void draw()
{

}


class Race
{
  ArrayList<Car> cars = new ArrayList<Car>();
  ArrayList<Car> placements = new ArrayList<Car>();
  int endX, endY = 0;

  Race(int size, int startX, int startY, int endX, int endY)
  {
    for(int i = 0; i < size; i++)
    {
      cars.add(new Car(startX, startY));
    }
    this.endX = endX;
    this.endY = endY;
  }

  void runOnce()
  {
    for (Car car : cars)
    {
      car.move(CAR_SPEED);
    }
  }

  ArrayList<Car> getPlacements()
  {
    ArrayList<Car> placements = new ArrayList<Car>();
    for(Car car : cars)
    {
      float distance = dist(car.x, car.y, endX, endY);
      for(int i = 0; i < size; i
    }
  }
}

class Car
{
  int x, y = 0;
  float dir = 0;
  Brain brain = new Brain(BRAIN_SIZE);

  Car(int startX, int startY)
  {
    x = startX;
    y = startY;
  }

  void move(int spd)
  {
    if (brain.next() != null)
    {
      dir = brain.curr;
      x += (Math.sin(dir) * spd);
      y -= (Math.cos(dir) * spd);
    }
  }
}


class Brain
{
  FloatList data = new FloatList();
  Float curr = 0.0;
  int index = 0;

  Brain(int size)
  {
    for(int i = 0; i < size; i++)
    {
      data.append(random(0, 1));
    }
  }

  Brain(Brain parent)
  {
    for(float n : parent.data)
    {
      if (random(0, 1) < MUTATION_CHANCE)
      {
        data.append(n * random(MUTATION_MIN, MUTATION_MAX));
      }
      else data.append(n);
    }
  }

  Float next()
  {
    if (index < data.size())
    {
      curr = data.get(index);
      index++;
    }
    else return null;
    return curr;
  }
}