Can you ask it for something more complicated like the traveling salesman implementation (which is NP hard yes but more efficient algorithms exist)?
It gave me a genetic algorithm:
// Define a class for representing a single city in the TSP
class City {
constructor(public x: number, public y: number) {}
// Calculate the distance to another city
public distanceTo(city: City): number {
const dx = this.x - city.x;
const dy = this.y - city.y;
return Math.sqrt(dx * dx + dy * dy);
}
}
// Define a class for representing a solution to the TSP
class Tour {
private cities: City[];
private fitness = 0;
private distance = 0;
constructor(tour?: City[]) {
if (tour) {
this.cities = tour;
} else {
this.cities = [];
}
}
// Add a city to the tour
public addCity(city: City) {
this.cities.push(city);
}
// Get the tour as an array of cities
public getTour(): City[] {
return this.cities;
}
// Get the fitness of the tour (lower is better)
public getFitness(): number {
if (this.fitness === 0) {
this.fitness = 1 / this.getDistance();
}
return this.fitness;
}
// Get the total distance of the tour
public getDistance(): number {
if (this.distance === 0) {
let tourDistance = 0;
// Loop through all cities in the tour and sum the distances
for (let i = 0; i < this.cities.length; i++) {
const fromCity = this.cities[i];
const toCity = this.cities[0];
if (i + 1 < this.cities.length) {
toCity = this.cities[i + 1];
}
tourDistance += fromCity.distanceTo(toCity);
}
this.distance = tourDistance;
}
return this.distance;
}
// Generate a random tour
public generateIndividual(): Tour {
const newTour = new Tour();
for (let i = 0; i < Tour.numberOfCities(); i++) {
newTour.addCity(Tour.getCity(i));
}
return newTour.shuffle();
}
// Shuffle the cities in the tour
public shuffle(): Tour {
const newTour = new Tour(this.cities);
const currentIndex = newTour.cities.length;
let temporaryValue;
let randomIndex;
// While there remain elements to shuffle...
while (currentIndex !== 0) {
// Pick a remaining element...
randomIndex = Math.floor(Math.random() * currentIndex);
currentIndex -= 1;
// And swap it with the current element
temporaryValue = newTour.cities[currentIndex];
newTour.cities[currentIndex] = newTour.cities[randomIndex];
newTour.cities[randomIndex] = temporaryValue;
}
return
...
It stopped here and continued when I asked it to but I stopped here because I don't want to exceed the HN limit.
It gave me a genetic algorithm:
// Define a class for representing a single city in the TSP class City { constructor(public x: number, public y: number) {}
}// Define a class for representing a solution to the TSP class Tour { private cities: City[]; private fitness = 0; private distance = 0;
It stopped here and continued when I asked it to but I stopped here because I don't want to exceed the HN limit.