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A core library to help implement two players games.

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package com.fathzer.games.ai.toys;

import java.util.List;

import com.fathzer.games.MoveGenerator;
import com.fathzer.games.MoveGenerator.MoveConfidence;
import com.fathzer.games.Status;
import com.fathzer.games.ai.AI;
import com.fathzer.games.ai.evaluation.Evaluation;
import com.fathzer.games.ai.evaluation.Evaluator;

/**
 * A very basic {@link AI} that that gives to a move the best score according to a given evaluator after the opponent played.
 * 
Of course in complex games like chess, the move chosen by this engine may be far for the best one due to
 * horizon effect.
 * @param  The type of moves
 * @param  The type of board
 */
public class NaiveAI> extends BasicAI {
	private final Evaluator evaluator;
	
	/** Constructor
	 * @param board The board
	 * @param evaluator The evaluator to use
	 */
	public NaiveAI (B board, Evaluator evaluator) {
		super(board);
		this.evaluator = evaluator;
	}
	
	@Override
	protected Evaluation getEvaluation(M move) {
		return evaluator.toEvaluation(evaluate(move));
	}

	int evaluate(M move) {
		// Play the evaluated move
		evaluator.prepareMove(board, move);
		board.makeMove(move, MoveConfidence.LEGAL);
		try {
			evaluator.commitMove();
			// Gets the opponent responses
			final List moves = board.getLegalMoves();
			if (moves.isEmpty()) {
				// End of game
				final Status status = board.getEndGameStatus();
				return status == Status.DRAW ? 0 : evaluator.getWinScore(1);
			}
			int min = 0;
			for (M m : moves) {
				// For all opponent responses
				final int value = evaluateOpponentMove(board, m);
				if (value