public Object getValueAt(int row, int col) {
BattleResults statistics = results[row];
switch (col) {
case 0:
{
int place = row + 1;
while (place < getRowCount() && statistics.getScore() == results[place].getScore()) {
place++;
}
return StringUtil.getPlacementString(place);
}
case 1:
return statistics.getTeamLeaderName();
case 2:
String percent = "";
if (totalScore != 0) {
percent =
" ("
+ NumberFormat.getPercentInstance().format(statistics.getScore() / totalScore)
+ ")";
}
return "" + (int) (statistics.getScore() + 0.5) + percent;
case 3:
return "" + (int) (statistics.getSurvival() + 0.5);
case 4:
return "" + (int) (statistics.getLastSurvivorBonus() + 0.5);
case 5:
return "" + (int) (statistics.getBulletDamage() + 0.5);
case 6:
return "" + (int) (statistics.getBulletDamageBonus() + 0.5);
case 7:
return "" + (int) (statistics.getRamDamage() + 0.5);
case 8:
return "" + (int) (statistics.getRamDamageBonus() + 0.5);
case 9:
return "" + statistics.getFirsts();
case 10:
return "" + statistics.getSeconds();
case 11:
return "" + statistics.getThirds();
default:
return "";
}
}
/**
* Function for counting the sum of the scores gathered by the robots.
*
* @return The sum.
*/
private double countTotalScore() {
double totalScore = 0;
for (BattleResults result : results) {
totalScore += result.getScore();
}
return totalScore;
}
private BattleResultsWrapper(BattleResults results) {
super(
results.getTeamLeaderName(),
results.getRank(),
results.getScore(),
results.getSurvival(),
results.getLastSurvivorBonus(),
results.getBulletDamage(),
results.getBulletDamageBonus(),
results.getRamDamage(),
results.getRamDamageBonus(),
results.getFirsts(),
results.getSeconds(),
results.getThirds());
}
public void runGA(int populationSize, int generationSize, int genomeSize) {
int generation = 1;
int parentsSelected = 5;
BattleResults[] results;
ArrayList<String> genomePaths = GAHelper.generatePopulation(populationSize, genomeSize);
for (String genomePath : genomePaths) {
Genome selected = GenomeIO.load(genomePath);
RobotGenerator.compile(selected);
String robotName = RobotGenerator.getClassPath(selected);
RobotSpecification[] selectedRobots =
engine.getLocalRepository(robotName + ",sample.RamFire");
BattleSpecification battleSpec = new BattleSpecification(1, battlefield, selectedRobots);
engine.runBattle(battleSpec, true);
results = battleObserver.getResults();
BattleResults result = results[0]; // Index 0 will always be the index of our generated Robot
// Evaluate fitness - Keeping it simple for now (fitness = score)
selected.setFitness(new Double(result.getScore()));
GenomeIO.save(selected);
System.out.println(
String.format(
"Genome result: generation:%d id:%d - FITNESS:%f",
selected.getGeneration(), selected.getId(), selected.getFitness()));
}
while (generation != generationSize) {
generation++;
genomePaths =
GAHelper.produceNextGeneration(generation, parentsSelected, populationSize, genomeSize);
for (String genomePath : genomePaths) {
Genome selected = GenomeIO.load(genomePath);
RobotGenerator.compile(selected);
String robotName = RobotGenerator.getClassPath(selected);
RobotSpecification[] selectedRobots =
engine.getLocalRepository(robotName + ",sample.RamFire");
BattleSpecification battleSpec = new BattleSpecification(1, battlefield, selectedRobots);
engine.runBattle(battleSpec, true);
results = battleObserver.getResults();
BattleResults result =
results[0]; // Index 0 will always be the index of our generated Robot
// Evaluate fitness - Keeping it simple for now (fitness = score)
selected.setFitness(new Double(result.getScore()));
GenomeIO.save(selected);
System.out.println(
String.format(
"Genome result: generation:%d id:%d - FITNESS:%f",
selected.getGeneration(), selected.getId(), selected.getFitness()));
}
}
engine.close();
System.exit(0);
}