package org.ggp.base.player.gamer.statemachine.sample;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import org.ggp.base.apps.player.detail.DetailPanel;
import org.ggp.base.apps.player.detail.SimpleDetailPanel;
import org.ggp.base.player.gamer.event.GamerSelectedMoveEvent;
import org.ggp.base.player.gamer.exception.GamePreviewException;
import org.ggp.base.player.gamer.statemachine.StateMachineGamer;
import org.ggp.base.util.game.Game;
import org.ggp.base.util.statemachine.MachineState;
import org.ggp.base.util.statemachine.Move;
import org.ggp.base.util.statemachine.StateMachine;
import org.ggp.base.util.statemachine.cache.CachedStateMachine;
import org.ggp.base.util.statemachine.exceptions.GoalDefinitionException;
import org.ggp.base.util.statemachine.exceptions.MoveDefinitionException;
import org.ggp.base.util.statemachine.exceptions.TransitionDefinitionException;
import org.ggp.base.util.statemachine.implementation.prover.ProverStateMachine;
/**
* SampleSearchLightGamer is a simple state-machine-based Gamer. It will,
* to the best of its ability, never pick a move which will give its opponent
* a possible one-move win. It will also spend up to two seconds looking for
* one-move wins it can take. This makes it slightly more challenging than the
* RandomGamer, while still playing reasonably fast.
*
* Essentially, it has a one-move search-light that it shines out, allowing it
* to avoid moves that are immediately terrible, and also choose moves that are
* immediately excellent.
*
* This approach implicitly assumes that it is playing an alternating-play game,
* which is not always true. It will play simultaneous-action games less well.
* It also assumes that it is playing a zero-sum game, where its opponent will
* always force it to lose if given that option.
*
* This player is fairly good at games like Tic-Tac-Toe, Knight Fight, and Connect Four.
* This player is pretty terrible at most games.
*
* @author Sam Schreiber
*/
public final class SampleSearchLightGamer extends StateMachineGamer
{
/**
* Does nothing
*/
@Override
public void stateMachineMetaGame(long timeout) throws TransitionDefinitionException, MoveDefinitionException, GoalDefinitionException
{
// Do nothing.
}
private Random theRandom = new Random();
/**
* Employs a simple sample "Search Light" algorithm. First selects a default legal move.
* It then iterates through all of the legal moves in random order, updating the current move selection
* using the following criteria.
* <ol>
* <li> If a move produces a 1 step victory (given a random joint action) select it </li>
* <li> If a move produces a 1 step loss avoid it </li>
* <li> If a move allows a 2 step forced loss avoid it </li>
* <li> Otherwise select the move </li>
* </ol>
*/
@Override
public Move stateMachineSelectMove(long timeout) throws TransitionDefinitionException, MoveDefinitionException, GoalDefinitionException
{
StateMachine theMachine = getStateMachine();
long start = System.currentTimeMillis();
long finishBy = timeout - 1000;
List<Move> moves = theMachine.getLegalMoves(getCurrentState(), getRole());
Move selection = (moves.get(new Random().nextInt(moves.size())));
// Shuffle the moves into a random order, so that when we find the first
// move that doesn't give our opponent a forced win, we aren't always choosing
// the first legal move over and over (which is visibly repetitive).
List<Move> movesInRandomOrder = new ArrayList<Move>();
while(!moves.isEmpty()) {
Move aMove = moves.get(theRandom.nextInt(moves.size()));
movesInRandomOrder.add(aMove);
moves.remove(aMove);
}
// Go through all of the legal moves in a random over, and consider each one.
// For each move, we want to determine whether taking that move will give our
// opponent a one-move win. We're also interested in whether taking that move
// will immediately cause us to win or lose.
//
// Our main goal is to find a move which won't give our opponent a one-move win.
// We will also continue considering moves for two seconds, in case we can stumble
// upon a move which would cause us to win: if we find such a move, we will just
// immediately take it.
boolean reasonableMoveFound = false;
int maxGoal = 0;
for(Move moveUnderConsideration : movesInRandomOrder) {
// Check to see if there's time to continue.
if(System.currentTimeMillis() > finishBy) break;
// If we've found a reasonable move, only spend at most two seconds trying
// to find a winning move.
if(System.currentTimeMillis() > start + 2000 && reasonableMoveFound) break;
// Get the next state of the game, if we take the move we're considering.
// Since it's our turn, in an alternating-play game the opponent will only
// have one legal move, and so calling "getRandomJointMove" with our move
// fixed will always return the joint move consisting of our move and the
// opponent's no-op. In a simultaneous-action game, however, the opponent
// may have many moves, and so we will randomly pick one of our opponent's
// possible actions and assume they do that.
MachineState nextState = theMachine.getNextState(getCurrentState(), theMachine.getRandomJointMove(getCurrentState(), getRole(), moveUnderConsideration));
// Does the move under consideration end the game? If it does, do we win
// or lose? If we lose, don't bother considering it. If we win, then we
// definitely want to take this move. If its goal is better than our current
// best goal, go ahead and tentatively select it
if(theMachine.isTerminal(nextState)) {
if(theMachine.getGoal(nextState, getRole()) == 0) {
continue;
} else if(theMachine.getGoal(nextState, getRole()) == 100) {
selection = moveUnderConsideration;
break;
} else {
if (theMachine.getGoal(nextState, getRole()) > maxGoal)
{
selection = moveUnderConsideration;
maxGoal = theMachine.getGoal(nextState, getRole());
}
continue;
}
}
// Check whether any of the legal joint moves from this state lead to
// a loss for us. Again, this only makes sense in the context of an alternating
// play zero-sum game, in which this is the opponent's move and they are trying
// to make us lose, and so if they are offered any move that will make us lose
// they will take it.
boolean forcedLoss = false;
for(List<Move> jointMove : theMachine.getLegalJointMoves(nextState)) {
MachineState nextNextState = theMachine.getNextState(nextState, jointMove);
if(theMachine.isTerminal(nextNextState)) {
if(theMachine.getGoal(nextNextState, getRole()) == 0) {
forcedLoss = true;
break;
}
}
// Check to see if there's time to continue.
if(System.currentTimeMillis() > finishBy) {
forcedLoss = true;
break;
}
}
// If we've verified that this move isn't going to lead us to a state where
// our opponent can defeat us in one move, we should keep track of it.
if(!forcedLoss) {
selection = moveUnderConsideration;
reasonableMoveFound = true;
}
}
long stop = System.currentTimeMillis();
notifyObservers(new GamerSelectedMoveEvent(moves, selection, stop - start));
return selection;
}
@Override
public void stateMachineStop() {
// Do nothing.
}
/**
* Uses a CachedProverStateMachine
*/
@Override
public StateMachine getInitialStateMachine() {
return new CachedStateMachine(new ProverStateMachine());
}
@Override
public String getName() {
return "SampleSearchLight";
}
@Override
public DetailPanel getDetailPanel() {
return new SimpleDetailPanel();
}
@Override
public void preview(Game g, long timeout) throws GamePreviewException {
// Do nothing.
}
@Override
public void stateMachineAbort() {
// Do nothing.
}
}