private void UpdateEnemyInfo(EnemyInfo enemyInfoToUpdate, ScannedRobotEvent e)
{
var currentTargetPosition =
Utilities.CalculateRobotPosition(_position, Utils.NormalAbsoluteAngle(this.HeadingRadians + e.BearingRadians), e.Distance);
enemyInfoToUpdate.LastPosition = currentTargetPosition;
enemyInfoToUpdate.RecordedTime = Time;
enemyInfoToUpdate.LastDistance = e.Distance;
enemyInfoToUpdate.LastEnergy = e.Energy;
}
public SimpleAimBot()
: base()
{
var nrStatesQLearning = 9;
ResetFirePowerLevels();
_enemy = new EnemyInfo();
_robotController = new AbstractRobot(this);
if (!_hasCreatedScores)
{
_aimLearner = new QLearning(
Segmentation.None
| Segmentation.DistanceClose | Segmentation.DistanceFar |
Segmentation.VelocityFast | Segmentation.VelocitySlow
,
nrStatesQLearning, 0.0d);
//Make sure discount factor is 1, as we will use temperature as the exploration rate
_aimLearner.DiscountFactor = 1.0f;
_aimLearner.Temperature = .2f;
_aimLearner.TemperatureDecraseAmount = _aimLearner.Temperature / 20f;
_aimLearner.MinTemperature = .005f;
_aimLearner.UseSoftmaxSelection = true;
//Start with positive scores so if robot keeps missing the scores go down
_aimLearner.UpdateAllLearningScores(1.0d);
_aimLearner.ResetFavorableActions(1);
_hasCreatedScores = true;
}
else
{
//Increase temperature slightly as opponent might switch dodging strategy
_aimLearner.Temperature += (.2f / 20f) * 5;
}
}
