protected override Reward Playout(WorldModel initialPlayoutState)
{
WorldModel model = initialPlayoutState.GenerateChildWorldModel();
List <GOB.Action> actions;
List <GOB.Action> executableActions = new List <GOB.Action>();
GOB.Action nextAction = null;
Reward reward = new Reward();
double heuristicValue;
double accumulatedHeuristicValue;
double bestValue, minValue;
SortedDictionary <double, GOB.Action> heuristicList = new SortedDictionary <double, GOB.Action>();
actions = model.GetActions();
while (!model.IsTerminal())
{
heuristicList.Clear();
executableActions.Clear();
heuristicValue = 0;
accumulatedHeuristicValue = 0;
bestValue = -1;
minValue = float.MaxValue;
if (actions.Count == 0)
{
break;
}
foreach (GOB.Action action in actions)
{
if (action.CanExecute(model))
{
accumulatedHeuristicValue += Math.Pow(Math.E, action.H(model));
executableActions.Add(action);
}
}
foreach (GOB.Action action in executableActions)
{
heuristicValue = Math.Pow(Math.E, action.H(model)) / accumulatedHeuristicValue;
if (!heuristicList.ContainsKey(heuristicValue))
{
heuristicList.Add(heuristicValue, action);
}
if (heuristicValue > bestValue)
{
bestValue = heuristicValue;
}
if (heuristicValue < minValue)
{
minValue = heuristicValue;
}
}
double randomNumber = GetRandomNumber(minValue, bestValue);
foreach (KeyValuePair <double, GOB.Action> actionHeuristic in heuristicList)
{
if (actionHeuristic.Key >= randomNumber)
{
nextAction = actionHeuristic.Value;
break;
}
}
if (nextAction == null)
{
break;
}
nextAction.ApplyActionEffects(model);
model.CalculateNextPlayer();
}
reward.PlayerID = model.GetNextPlayer();
reward.Value = model.GetScore();
return(reward);
}
protected virtual void Backpropagate(MCTSNode node, Reward reward)
{
//TODO: implement
throw new NotImplementedException();
}
