/*
* Encog(tm) Examples v3.0 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2011 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.examples.nonlinear.basicstrategy;
import org.encog.examples.nonlinear.basicstrategy.blackjack.Dealer;
import org.encog.examples.nonlinear.basicstrategy.blackjack.Table;
import org.encog.ml.genetic.BasicGeneticAlgorithm;
import org.encog.ml.genetic.GeneticAlgorithm;
import org.encog.ml.genetic.crossover.Splice;
import org.encog.ml.genetic.mutate.MutateShuffle;
import org.encog.ml.genetic.population.BasicPopulation;
import org.encog.ml.genetic.population.Population;
public class Play21 {
public static final int POPULATION_SIZE = 1000;
public static final double MUTATION_PERCENT = 0.1;
public static final double PERCENT_TO_MATE = 0.24;
public static final double MATING_POPULATION_PERCENT = 0.5;
public static final int CUT_LENGTH = 50;
public static void test() {
/*
* for(int i=0;i<52;i++) { System.out.print(identifyCard(i));
* System.out.print(" "); System.out.print(hasSoftValue(i));
* System.out.print(" "); System.out.print(softValue(i));
* System.out.print(" "); System.out.print(hardValue(i));
*
* System.out.println(); }
*/
Table table = new Table(1, new Dealer());
table.addPlayer(new Player(1000));
table.addPlayer(new Player(1000));
table.addPlayer(new Player(1000));
table.addPlayer(new Player(1000));
table.addPlayer(new Player(1000));
for (int i = 0; i < 10; i++) {
table.play();
}
}
private static void initPopulation(GeneticAlgorithm ga)
{
ScorePlayer score = new ScorePlayer();
ga.setCalculateScore(score);
Population population = new BasicPopulation(POPULATION_SIZE);
ga.setPopulation(population);
for (int i = 0; i < POPULATION_SIZE; i++) {
Player player = new Player(1000);
player.randomize();
final PlayerGenome genome = new PlayerGenome(ga, player);
ga.getPopulation().add(genome);
ga.calculateScore(genome);
}
population.sort();
}
public static void main(String[] args) {
GeneticAlgorithm genetic = new BasicGeneticAlgorithm();
initPopulation(genetic);
genetic.setMutationPercent(MUTATION_PERCENT);
genetic.setPercentToMate(PERCENT_TO_MATE);
genetic.setMatingPopulation(MATING_POPULATION_PERCENT);
genetic.setCrossover(new Splice(CUT_LENGTH));
genetic.setMutate(new MutateShuffle());
boolean done = false;
int iteration = 0;
while(!done)
{
iteration++;
genetic.iteration();
double thisSolution = genetic.getPopulation().getBest().getScore();
System.out.println(iteration + ": " + thisSolution);
}
}
}