Rock Paper Scissors Lizard Spock Game in Java on the SSaurel's Channel

RockPaperScissorsLizardSpock.java

import java.text.DecimalFormat;
import java.util.Arrays;
import java.util.List;
import java.util.Random;
import java.util.Scanner;

public class RockPaperScissorsLizardSpock {

  public enum Item {
    ROCK, PAPER, SCISSORS, LIZARD, SPOCK;

    public List<Item> losesTo;

    public boolean losesTo(Item other) {
      return losesTo.contains(other);
    }

    static {
      SCISSORS.losesTo = Arrays.asList(ROCK, SPOCK);
      ROCK.losesTo = Arrays.asList(PAPER, SPOCK);
      PAPER.losesTo = Arrays.asList(SCISSORS, LIZARD);
      SPOCK.losesTo = Arrays.asList(PAPER, LIZARD);
      LIZARD.losesTo = Arrays.asList(SCISSORS, ROCK);
    }
  }

  private static DecimalFormat DECIMAL_FORMATTER = new DecimalFormat(".##");
  public static final Random RANDOM = new Random();
  // stats for the game (you win / tie / computer win)
  private int[] stats = new int[] {0, 0, 0};
  // we use a Markov Chain for the AI of our computer
  private int[][] markovChain; // used just for the prev to current throws prediction
  private int nbThrows = 0;
  private Item last = null;

  private void init() {
    int length = Item.values().length;
    markovChain = new int[length][length];

    for (int i = 0; i < length; i++) {
      for (int j = 0; j < length; j++) {
        markovChain[i][j] = 0;
      }
    }
  }

  private void updateMarkovChain(Item prev, Item next) {
    markovChain[prev.ordinal()][next.ordinal()]++;
  }

  private Item nextMove(Item prev) {
    if (nbThrows < 1) {
      // first move => we can't use Markov Chain prediction
      // so we use a random on the Item list
      return Item.values()[RANDOM.nextInt(Item.values().length)];
    }

    // we try to predict next Item choosen by the user by reading data in our Markov Chain
    // for the prev entry in the array
    int nextIndex = 0;

    for (int i = 0; i < Item.values().length; i++) {
      int prevIndex = prev.ordinal();

      if (markovChain[prevIndex][i] > markovChain[prevIndex][nextIndex]) {
        nextIndex = i;
      }
    }

    // Item probably played by the user is in nextIndex
    Item predictedNext = Item.values()[nextIndex];

    // we choose amongst item for which this probably item loses
    List<Item> losesTo = predictedNext.losesTo;
    return losesTo.get(RANDOM.nextInt(losesTo.size()));
  }

  public void play() {
    init();

    Scanner in = new Scanner(System.in);
    System.out.print("Make your choice : ");

    while (in.hasNextLine()) {
      String input = in.nextLine();

      if ("STOP".equals(input))
        break;

      // read user choise
      Item choice;

      try {
        choice = Item.valueOf(input.toUpperCase());
      } catch (Exception e) {
        System.out.println("Invalid choice");
        continue;
      }

      Item aiChoice = nextMove(last);
      nbThrows++;

      // update Markov Chain
      if (last != null) {
        updateMarkovChain(last, choice);
      }

      last = choice;

      System.out.println("Computer choice : " + aiChoice);

      if (aiChoice.equals(choice)) {
        System.out.println(" ==> Tie !\n");
        stats[1]++;
      } else if(aiChoice.losesTo(choice)) {
        System.out.println(" ==> You win !\n");
        stats[0]++;
      } else {
        System.out.println(" ==> You lose !\n");
        stats[2]++;
      }

      System.out.print("Make your choice : ");
    }

    in.close();

    // display Stats
    System.out.println("\n");
    System.out.println("Win Stats");
    int total = stats[0] + stats[1] + stats[2];
    System.out.println("You : " + stats[0] + " - " + 
          DECIMAL_FORMATTER.format(stats[0] / (float) total * 100f) + "%");
    System.out.println("Tie : " + stats[1] + " - " + 
          DECIMAL_FORMATTER.format(stats[1] / (float) total * 100f) + "%");
    System.out.println("Computer : " + stats[2] + " - " + 
          DECIMAL_FORMATTER.format(stats[2] / (float) total * 100f) + "%");
  }

  public static void main(String[] args) {
    RockPaperScissorsLizardSpock rpsls = new RockPaperScissorsLizardSpock();
    rpsls.play();
  }

}