Package org.cspoker.ai.bots

Source Code of org.cspoker.ai.bots.BotRunner

/**
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
*  This program is distributed in the hope that it will be useful,
*  but WITHOUT ANY WARRANTY; without even the implied warranty of
*  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
*  GNU General Public License for more details.
*  You should have received a copy of the GNU General Public License
*  along with this program; if not, write to the Free Software
*  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
package org.cspoker.ai.bots;

import java.io.IOException;
import java.rmi.RemoteException;
import java.util.concurrent.ExecutorService;

import javax.security.auth.login.LoginException;

import net.jcip.annotations.NotThreadSafe;

import org.apache.log4j.Logger;
import org.cspoker.ai.bots.bot.Bot;
import org.cspoker.ai.bots.bot.BotFactory;
import org.cspoker.ai.bots.bot.gametree.mcts.MCTSBotFactory;
import org.cspoker.ai.bots.bot.gametree.mcts.nodes.MCTSShowdownRollOutNode;
import org.cspoker.ai.bots.bot.gametree.mcts.strategies.backpropagation.SampleWeightedBackPropStrategy;
import org.cspoker.ai.bots.bot.gametree.mcts.strategies.selection.MaxValueSelector;
import org.cspoker.ai.bots.bot.gametree.mcts.strategies.selection.SamplingSelector;
import org.cspoker.ai.bots.bot.gametree.mcts.strategies.selection.SamplingToFunctionSelector;
import org.cspoker.ai.bots.bot.gametree.mcts.strategies.selection.UCTSelector;
import org.cspoker.ai.bots.bot.gametree.search.expander.sampling.BucketSampler;
import org.cspoker.ai.bots.bot.gametree.search.expander.sampling.Sampler;
import org.cspoker.ai.bots.listener.BotListener;
import org.cspoker.ai.bots.listener.CSVLogListener;
import org.cspoker.ai.bots.listener.GameLimitingBotListener;
import org.cspoker.ai.bots.listener.KullbackLeiblerListener;
import org.cspoker.ai.bots.listener.ReSitInBotListener;
import org.cspoker.ai.bots.listener.SpeedTestBotListener;
import org.cspoker.ai.experiments.util.CombinationGenerator;
import org.cspoker.ai.opponentmodels.weka.WekaOptions;
import org.cspoker.ai.opponentmodels.weka.WekaRegressionModelFactory;
import org.cspoker.client.common.SmartClientContext;
import org.cspoker.client.common.SmartLobbyContext;
import org.cspoker.common.RemoteCSPokerServer;
import org.cspoker.common.api.lobby.event.TableCreatedEvent;
import org.cspoker.common.api.lobby.event.TableRemovedEvent;
import org.cspoker.common.api.lobby.listener.DefaultLobbyListener;
import org.cspoker.common.api.lobby.listener.LobbyListener;
import org.cspoker.common.api.shared.exception.IllegalActionException;
import org.cspoker.common.elements.player.PlayerId;
import org.cspoker.common.elements.table.TableConfiguration;
import org.cspoker.common.elements.table.TableId;
import org.cspoker.common.util.Log4JPropertiesLoader;
import org.cspoker.common.util.threading.GlobalThreadPool;
import org.cspoker.common.util.threading.SingleThreadRequestExecutor;

@NotThreadSafe
public class BotRunner implements LobbyListener {

  private static final int nbBigBlindsBuyIn = 0; //0 for Doyle's Game -> 200
  private static final TableConfiguration config = new TableConfiguration(100,
      0, false, true, true,0);

  public static final int nbGamesPerConfrontation = 10000;
  public static final int reportInterval = 2
  public final int nbExperiments = 1;
 
  public static int currentExperiment = 1;
  public int nbPlayersPerGame;
 
  static {
    Log4JPropertiesLoader
    .load("org/cspoker/ai/experiments/logging/log4j.properties");
  }

  private final static Logger logger = Logger.getLogger(BotRunner.class);

  private BotFactory[] botFactories;

  private SmartLobbyContext[] botLobbies;
  private PlayerId[] botIDs;

  protected SmartLobbyContext directorLobby;

  private ExecutorService executor;

  private volatile Bot[] bot;

  private volatile int[] botIndex;

  private BotListener speedMonitor;
  private CSVLogListener csvLogger;
  private volatile BotListener gameLimiter;
  private static KullbackLeiblerListener kullbackLeibler;
 
  private CombinationGenerator combinationgenerator;
  private final String expName;
  private final RemoteCSPokerServer cspokerServer;
 
  public static void create(RemoteCSPokerServer cspokerServer) { 
    kullbackLeibler = new KullbackLeiblerListener(reportInterval);  
//    new BotRunner(cspokerServer, "bucketSampler0.01VsRulebots");
    new BotRunner(cspokerServer, "MCTSBOTvsMCTSBOT10000", getBots());
  }
 
  public static BotFactory[] getBots() {
    try {
//      if(false){
//        //hide compiler warnings
//        throw new IOException();
//      }
//      if(false){
//        throw new ClassNotFoundException();
//      }
      WekaOptions configNoPersist = new WekaOptions();
      configNoPersist.setUseOnlineLearning(false);
     
      WekaOptions configPersist = new WekaOptions();
      configPersist.setContinuousLearning(true);
      configPersist.setModelCreationTreshold(8000);
      configPersist.setContinueAfterCreation(false);
      configPersist.setSolveConceptDrift(false);
     
      Sampler s = new BucketSampler(0.01);
//      Sampler s = new StochasticUniversalSampler(9);
//      Sampler s = new RouletteWheelSampler(9);
//      Sampler s = new RandomSampler(9);
     
      return new BotFactory[] {
//        new AlternatingBotFactory("AlternatingBot", 2000),
//        new CallBotFactory("CallBot"), // 62% precision, 71% accuracy
//        new CardBotFactory("CardBot"), // 60% precision, 71% accuracy
//        new HandBotFactory("HandBot"), // 41% accuracy
//        new FixedSampleMCTSBotFactory("MCTSBot",
//            WekaRegressionModelFactory.createForZip("org/cspoker/ai/opponentmodels/weka/models/model1.zip",
//                configNoPersist),
//            new SamplingToFunctionSelector(50,new UCTSelector(40000)),
//            new SamplingToFunctionSelector(50,new UCTPlusPlusSelector()),
//            new MaxValueSelector(),
//            new MCTSBucketShowdownNode.Factory(),
//            new MixedBackPropStrategy.Factory(
//                50,
//                new SampleWeightedBackPropStrategy.Factory(),
//                new MaxDistributionPlusBackPropStrategy.Factory()
//            ),s,
//            200,500,1000,3000),
        new MCTSBotFactory("MCTSBot NO LEARNING",
            WekaRegressionModelFactory.createForZip(
                "org/cspoker/ai/opponentmodels/weka/models/model1.zip", configNoPersist),
            new SamplingToFunctionSelector(50,new UCTSelector(2000)),
            new SamplingSelector(),
            new MaxValueSelector(),
            new MCTSShowdownRollOutNode.Factory(),
            new SampleWeightedBackPropStrategy.Factory(),
            s,
            500
        ),
        new MCTSBotFactory("MCTSBot",
            WekaRegressionModelFactory.createForZip(
                "org/cspoker/ai/opponentmodels/weka/models/model1.zip", configPersist/*, kullbackLeibler*/),
            new SamplingToFunctionSelector(50,new UCTSelector(20000)),
            new SamplingSelector(),
            new MaxValueSelector(),
            new MCTSShowdownRollOutNode.Factory(),
            new SampleWeightedBackPropStrategy.Factory(),
            s,
            500
        ),
//        new SearchBotFactory( // 42,5% accuracy
//            WekaRegressionModelFactory.createForZip("org/cspoker/ai/opponentmodels/weka/models/model1.zip", configNoPersist),
//            new ShowdownRolloutNode.Factory(new DistributionRollout4.Factory()), s,                       
//            200, 400, 1000, 3000, 0.0, false, true
//        )
        //          new MCTSBotFactory(
        //              "MCTS Bot",
        //              new WekaRegressionModelFactory("/home/guy/Werk/thesis/weka-3-6-0/model1"),
        //              new SamplingToFunctionSelector(20,new UCTSelector(40000)),
        //              new SamplingSelector(),
        //              new MaxValueSelector(),
        //              new MCTSBucketShowdownNode.Factory(),
        //              new SampleWeightedBackPropStrategy.Factory(),
        //              2000
        //          ),
        //          new MCTSBotFactory(
        //              "Bot 2",
        //              new WekaRegressionModelFactory("/home/guy/Werk/thesis/weka-3-6-0/model1"),
        //              new SamplingToFunctionSelector(10,new UCTPlusSelector(2000,0.5)),
        //              new MixedSelectionStrategy(new SamplingSelector(), new MinValueSelector(),0.95),
        //              new MaxUnderValueSelector(2),
        //              new MCTSBucketShowdownNode.Factory(),
        //              new MixtureBackPropStrategy.Factory(new MaxUnderValueSelector(2)),
        //              250
        //          ),
        //          new MCTSBotFactory(
        //              "Bot 3",
        //              new WekaRegressionModelFactory("/home/guy/Werk/thesis/weka-3-6-0/model1"),
        //              new SamplingToFunctionSelector(10,new UCTSelector(20000)),
        //              new MixedSelectionStrategy(new SamplingSelector(), new MinValueSelector(),0.95),
        //              new MaxUnderValueSelector(2),
        //              new MCTSBucketShowdownNode.Factory(),
        //              new MixtureBackPropStrategy.Factory(new MaxUnderValueSelector(2)),
        //              250
        //          ),
        //          new MCTSBotFactory(
        //              "Bot 4",
        //              new WekaRegressionModelFactory("/home/guy/Werk/thesis/weka-3-6-0/model1"),
        //              new SamplingToFunctionSelector(10,new UCTPlusSelector(20000,0.5)),
        //              new MixedSelectionStrategy(new SamplingSelector(), new MinValueSelector(),0.95),
        //              new MaxUnderValueSelector(2),
        //              new MCTSBucketShowdownNode.Factory(),
        //              new MixtureBackPropStrategy.Factory(new MaxUnderValueSelector(2)),
        //              250
        //          ),
        //          new MCTSBotFactory(
        //              "Bot B",
        //              new WekaRegressionModelFactory("/home/guy/Werk/thesis/weka-3-6-0/model1"),
        //              new SamplingToFunctionSelector(new UCTSelector(5000)),
        //              new SampleProportionateSelector(),
        //              new MCTSBucketShowdownNode.Factory(),
        //              50),
      };
         
    } catch (IOException e) {
      throw new IllegalStateException(e);
    } catch (ClassNotFoundException e) {
      throw new IllegalStateException(e);
    }
  }
 
  public BotRunner(RemoteCSPokerServer cspokerServer, BotFactory[] bots) {
    this(cspokerServer, "bots", bots);
  }
 
  public BotRunner(RemoteCSPokerServer cspokerServer, String expName, BotFactory[] bots) {
    this.expName = expName;
    this.cspokerServer = cspokerServer;
    this.botFactories = bots;
   
    prepareBots();
    iterateBots();
  }
 
  private void prepareBots() {
    try {
      nbPlayersPerGame = botFactories.length;//or a constant
      bot = new Bot[nbPlayersPerGame];
      botIndex = new int[nbPlayersPerGame];
 
      botLobbies = new SmartLobbyContext[botFactories.length];
      botIDs = new PlayerId[botFactories.length];
     
      SmartClientContext director = new SmartClientContext(cspokerServer
          .login("director", "test"));
      directorLobby = director.getLobbyContext(BotRunner.this);
 
      for (int i = 0; i < botFactories.length; i++) {
        SmartClientContext clientContext = new SmartClientContext(
            cspokerServer.login(botFactories[i].toString(), "test"));
        botLobbies[i] = clientContext.getLobbyContext(new DefaultLobbyListener());
        botIDs[i] = clientContext.getAccountContext().getPlayerID();
      }
 
      executor = SingleThreadRequestExecutor.getInstance();
 
      combinationgenerator = new CombinationGenerator(botFactories.length, nbPlayersPerGame);
    } catch (LoginException e) {
      throw new IllegalStateException("Login Failed", e);
    } catch (RemoteException e) {
      logger.error(e);
      throw new IllegalStateException("Server setup failed.", e);
    } catch (IllegalActionException e) {
      logger.error(e);
      throw new IllegalStateException("Server setup failed.", e);
    }
  }

  private void iterateBots() {
    if(combinationgenerator.hasMore()){
      botIndex = combinationgenerator.getNext();
      resetStateAndStartPlay();
    } else{
      shutdown();
    }
  }

  private void resetStateAndStartPlay() {
    logger.info("Experiment " + expName + "-" + currentExperiment + " ("
        + nbGamesPerConfrontation + " deals) starting...");
    gameLimiter = new GameLimitingBotListener(this, nbGamesPerConfrontation);
    speedMonitor = new SpeedTestBotListener(reportInterval, this);
    csvLogger = new CSVLogListener(reportInterval,this, expName+"-"+currentExperiment++);
    playOnNewtable();
  }

  private void playOnNewtable() {
    try {
      String tableName = botFactories[botIndex[0]].toString();
      for (int i = 1; i < nbPlayersPerGame; i++) {
        tableName += " vs " + botFactories[botIndex[i]].toString();
      }
      TableId tableId = directorLobby.createHoldemTable(tableName, config).getId();
      int buyIn = nbBigBlindsBuyIn*config.getBigBlind();

      bot[0] = botFactories[botIndex[0]].createBot(botIDs[botIndex[0]], tableId,
          botLobbies[botIndex[0]], buyIn, executor,
          new ReSitInBotListener(this), csvLogger,  /*speedMonitor,*/ gameLimiter /*, kullbackLeibler*/);
      bot[0].start();
      for (int i = 1; i < nbPlayersPerGame; i++) {
        bot[i] = botFactories[botIndex[i]].createBot(botIDs[botIndex[i]],
            tableId, botLobbies[botIndex[i]], buyIn, executor);
        bot[i].start();
      }
      bot[0].startGame();
    } catch (RemoteException e) {
      logger.error(e);
      throw new IllegalStateException("Server setup failed.", e);
    } catch (IllegalActionException e) {
      logger.error(e);
      throw new IllegalStateException("Server setup failed.", e);
    }
  }

  private void shutdown() {
    logger.info("Experiment " + expName + "-" + (currentExperiment - 1)
        + " successfully ended!");
    if (currentExperiment <= nbExperiments) {
      this.botFactories = getBots();
      prepareBots();
      iterateBots();
    } else {
      executor.shutdownNow();
      GlobalThreadPool.getInstance().shutdownNow();
    }
  }

  public void onTableCreated(TableCreatedEvent tableCreatedEvent) {
    logger
    .debug(tableCreatedEvent.getTable().getName()
        + " table created.");
  }

  public void onTableRemoved(TableRemovedEvent tableRemovedEvent) {
    logger.debug("Table " + tableRemovedEvent.getTableId() + " removed.");
  }

  public void respawnBots() {
    stopRunningBots();
    playOnNewtable();
  }

  private void stopRunningBots() {
    for (int i = 0; i < nbPlayersPerGame; i++) {
      bot[i].stop();
    }
  }

  public void moveToNextCombination() {
    stopRunningBots();
    iterateBots();
  }

  public BotFactory getBotFactory(int i) {
    return botFactories[botIndex[i]];
  }

  public Bot getBot(int i) {
    return bot[i];
  }

  public TableConfiguration getConfig() {
    return config;
  }

}
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