How can I implement weighted random selection in Java using NavigableMaps?

Random Weighted Selection in Java

In the realm of programming, weighted random selection refers to choosing an item from a set where the probability of selection is directly linked to an associated weight. This technique finds applications in scenarios such as simulations and lotteries, where biased selection based on probabilities is desired.

To address the problem of weighted random selection in Java, we introduce the concept of a NavigableMap. This data structure allows us to map weights to corresponding items and traverse the map in ascending order. With the help of a random number generator, we can efficiently select items with probabilities proportional to their weights.

Let's consider an example of selecting animals with varying probabilities:

• Dog: 40%
• Cat: 35%
• Horse: 25%

To implement weighted random selection using a NavigableMap, we can create a class:

public class RandomCollection<E> {
    //NavigableMap to store weights and corresponding items
    private final NavigableMap<Double, E> map = new TreeMap<>();
    //Random instance for generating random weights
    private final Random random;
    //Total sum of weights
    private double total = 0;

    public RandomCollection() {
        this(new Random());
    }

    public RandomCollection(Random random) {
        this.random = random;
    }

    //Add an item to the collection with its weight
    public RandomCollection<E> add(double weight, E result) {
        if (weight <= 0) return this;
        total += weight;
        map.put(total, result);
        return this;
    }

    //Select a random item based on weights
    public E next() {
        double value = random.nextDouble() * total;
        return map.higherEntry(value).getValue();
    }
}

To demonstrate, let's create and populate a RandomCollection with the animal weights:

RandomCollection<String> rc = new RandomCollection<>();
rc.add(40, "dog")
  .add(35, "cat")
  .add(25, "horse");

Now, we can repeatedly call the next() method to select animals based on their assigned weights:

for (int i = 0; i < 10; i++) {
    System.out.println(rc.next());
}

This code will produce a sequence of animal names, with the probability of selecting each animal proportionate to its weight. By utilizing the power of NavigableMaps and randomness, we can effectively implement weighted random selection in Java, allowing for biased outcomes based on predefined probabilities.

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