public void SetAsRoot(Distribution <State> d)
{
Parent = null;
Belief = d;
}
/// <summary>
/// Add a child node at the end of the children list
/// </summary>
/// <param name="childNode"></param>
public void AddChild(ActionNode childNode)
{
Children.Add(childNode);
}
//
/// <summary>
/// Function that perform one exploration of the tree, and make it grow by a pair of action & belief nodes
/// </summary>
/// <param name="maxDepth"></param>
public void GrowTree(int maxDepth, float gama, float C)
{
BeliefNode beliefNode = Root;
Root.IncrementOccurrence();
// Explore the tree until it reaches the finish point or the number of iteration is too high
int depth = 1;
ActionNode actionNode;
Action action;
State state;
bool stocking = true;
while (depth < maxDepth & !beliefNode.IsTerminal())
{
// Pick a state in the belief of the actual belief node
state = beliefNode.Belief.GetNormalisedCopy().Draw();
// Draw the next action
action = beliefNode.DrawAction(state, stocking, C);
// If the new node is not in the children, it is added, else its occurrence is incremented
actionNode = beliefNode.SearchChildren(action);
if (actionNode == null)
{
actionNode = new ActionNode(action, beliefNode);
if (stocking)
{
beliefNode.AddChild(actionNode);
}
}
else
{
actionNode.IncrementOccurrence();
}
// Get a new state of the system
state = _markovModel.ApplyTransition(state, action).Draw();
Observation observation = _markovModel.GetAllObservations(state).Draw();
// If the new node is not in the children, it is added, else its occurrence is incremented
beliefNode = actionNode.SearchChildren(observation);
if (beliefNode == null)
{
beliefNode = new BeliefNode(observation, actionNode, _markovModel);
if (stocking)
{
actionNode.AddChild(beliefNode);
}
stocking = false;
}
else
{
beliefNode.IncrementOccurrence();
}
beliefNode.AddState(state);
depth++;
}
beliefNode.UpdateValue(gama);
}
