public actionType selectAction()
{
// get value for every action;
double[] values = _actionValue.value(state, _possibleActions);
//Console.WriteLine(String.Join(",", values));
if (_actionValue.getRecommendedExplorationMode() == explorationMode.suspendExploration)
{
return(explorationFreePolicy.selectAction(_possibleActions, values.ToList()));
}
else
{
return(_policy.selectAction(_possibleActions, values.ToList()));
}
}
private static double heuristic(stateType state, ActionValue <stateType, actionType> model, List <actionType> availableActions)
{
return(-model.value(state, availableActions).Max() / 2 + 0.5);
//double bestDist = double.PositiveInfinity;
//foreach (int[] goal in goals)
//{
// int[] diff = arraySubtract(goal, state);
// double taxiDist = 0;
// foreach (int i in diff)
// {
// taxiDist += Math.Abs(i);
// }
// if (taxiDist < bestDist)
// bestDist = taxiDist;
//}
//return bestDist*0.01;
}
public override double[] value(int[] state, List <int[]> actions)
{
return(alloLearner.value(new int[2] {
state[0], state[1]
}, actions));
}