/// <summary>
/// Generates a node's successors.
/// </summary>
/// <param name='currentNode'>
/// Current node.
/// </param>
void generateNodeSuccessors(ref ARAstarNode currentNode)
{
List <DefaultAction> possibleTransitions = new List <DefaultAction> ();
selectedPlanningDomain.generateTransitions(ref currentNode.action.state, ref currentNode.previousState, ref goalNode.action.state, ref possibleTransitions);
ARAstarNode nextNode;
foreach (DefaultAction successorAction in possibleTransitions)
{
DefaultAction nextAction = successorAction;
//float newg = currentNode.g + nextAction.cost;
float newh = selectedPlanningDomain.ComputeHEstimate(nextAction.state, goalNode.action.state);
if (!Visited.ContainsState(nextAction.state))
{
nextNode = new ARAstarNode(Mathf.Infinity, newh, currentNode.action.state, nextAction);
}
else
{
nextNode = Visited.nodeForState(nextAction.state);
}
nextNode.weightExpanded = inflationFactor;
if (currentNode.highPriority > 0)
{
if (!Plan.ContainsState(nextNode.action.state))
{
nextNode.highPriority = currentNode.highPriority - 1;
}
}
UpdateVertex(nextNode);
}
}
void UpdateState(ref ADAstarNode currentNode)
{
PlanningDomainBase domain = default(PlanningDomainBase);
List <DefaultAction> possibleTransitions = new List <DefaultAction>();
float score = 0;
foreach (PlanningDomainBase d in _planningDomain)
{
if (d.evaluateDomain(ref startNode.action.state) > score)
{
score = d.evaluateDomain(ref startNode.action.state);
domain = d;
}
}
if (!currentNode.alreadyExpanded)
{
currentNode.g = Mathf.Infinity;
}
if (!domain.isAGoalState(ref currentNode.action.state, ref goalNode.action.state))
{
possibleTransitions.Clear();
domain.generateTransitions(ref currentNode.action.state, ref currentNode.previousState, ref goalNode.action.state, ref possibleTransitions);
// Determine min(c(s,s')+g(s')) for rhs for every successor
float min_rhs = Mathf.Infinity;
foreach (DefaultAction action in possibleTransitions)
{
DefaultAction nextAction = action;
float newh = domain.ComputeEstimate(ref startNode.action.state, ref nextAction.state, "h");
float newg = domain.ComputeEstimate(ref nextAction.state, ref goalNode.action.state, "g");
//g is calculated as the distance to the goal, just use a dummy value -1.0 and calculate the distance next
ADAstarNode nextNode = new ADAstarNode(newg, newh, ref currentNode.action.state, ref nextAction);
if ((nextAction.cost + nextNode.g) < min_rhs)
{
min_rhs = nextAction.cost + nextNode.g;
}
}
currentNode.rhs = min_rhs;
float[] keys = GetKey(currentNode);
currentNode.key1 = keys[0]; currentNode.key2 = keys[1];
}
Debug.Log("A");
//If open contains node, remove it.
//foreach(KeyValuePair<DefaultState, ADAstarNode> keyval in Open)
for (int i = 0; i < Open.Count; ++i)
{
if (Open[i].Key != null)
{
if (domain.equals(Open[i].Key, currentNode.action.state, false))
{
Open.RemoveAt(i); currentNode.alreadyExpanded = true;
}
}
}
//Open = BackUp;
//KeyValuePair<DefaultState, ADAstarNode> keyval = new KeyValuePair<DefaultState, ADAstarNode>(currentNode.action.state, currentNode);
//if(Open.Contains(keyval)) {Open.Remove(keyval); currentNode.alreadyExpanded = true;}
if (currentNode.g != currentNode.rhs)
{
bool containsNode = false;
//foreach(DefaultState key in Closed.Keys)
//{
//if(domain.equals(key, currentNode.action.state))
//if(domain.equals(key, currentNode.action.state, false))
//{ containsNode = true; break; }
//}
if (Closed.ContainsKey(currentNode.action.state))
{
containsNode = true;
}
if (!containsNode)
{
//Generate all predecessors to keep expanding the open list
generateNodePredecessors(ref domain, ref currentNode);
Open.Add(new KeyValuePair <DefaultState, ADAstarNode>(currentNode.action.state, currentNode));
//Sort by priority keys
Open.Sort(ADAstartCopareCost.CompareCost);
}
else
{
Incons.Add(currentNode.action.state, currentNode);
}
}
}
} //end _ComputePlan
public bool _computeOneStep(ref DefaultState startState, ref DefaultState idealGoalState, Dictionary <DefaultState, BestFirstSearchNode> stateMap, ref DefaultState actualStateReached, float maxTime)
{
//SortedList<BestFirstSearchNode<PlanningState, PlanningAction>> openSet = new SortedList<BestFirstSearchNode<PlanningState, PlanningAction>>(new CompareCosts<PlanningState, PlanningAction>());
PlanningDomainBase domain = default(PlanningDomainBase);
// int index = 0;
float score = 0;
foreach (PlanningDomainBase d in _planningDomain)
{
if (d.evaluateDomain(ref startState) > score)
{
score = d.evaluateDomain(ref startState);
domain = d;
}
}
/***** TEST of MULTIPLE DOMAINS *****/
//domain = _planningDomain.ElementAt(1);
/***********************************/
if (OneStepNeedsUpdate)
{
Debug.Log("Plan finished, clearing Lists. Plan again");
stateReached = startState;
stateMap.Clear();
openSet.Clear();
OneStepNeedsUpdate = false;
initPlanner = true;
return(false);
}
//Debug.Log("maxNumNodesToExpand = " + _maxNumNodesToExpand);
if ((numNodesExpanded == _maxNumNodesToExpand) || (openSet.Count == 0))
{
OneStepNeedsUpdate = true;
}
else
{
numNodesExpanded++;
openSet.Sort(CompareCosts.CompareCost);
// get a copy of the first element of the open set (i.e. about to pop it, but only if we get past the next if-statement).
BestFirstSearchNode x = (openSet.ElementAt(0));
openSet.Remove(openSet.ElementAt(0));
score = 0;
foreach (PlanningDomainBase d in _planningDomain)
{
if (d.evaluateDomain(ref x.action.state) > score)
{
score = d.evaluateDomain(ref x.action.state);
domain = d;
}
}
/***** TEST of MULTIPLE DOMAINS *****/
/*
* //if (stateMap.Count > 100)
* if (numNodesExpanded > 5)
* {
* //Debug.Log("We change of domain at time " + Time.time);
* domain = _planningDomain.ElementAt(0);
* }
* /***********************************/
// ask the user if this node is a goal state. If so, then finish up.
//if ((_planningDomain as PlanningDomainBase<PlanningState>).isAGoalState(ref x.action.state, ref idealGoalState))
if (domain.isAGoalState(ref x.action.state, ref idealGoalState))
{
actualStateReached = x.action.state;
//Debug.Log("goal reached");
OneStepNeedsUpdate = true;
return(true);
}
if (stateMap.ContainsKey(x.action.state))
{
stateMap[x.action.state].alreadyExpanded = true;
}
// ask the user to generate all the possible actions from this state.
List <DefaultAction> possibleActions = new List <DefaultAction>();
possibleActions.Clear();
//Debug.Log("generating transitions");
domain.generateTransitions(ref x.action.state, ref x.previousState, ref idealGoalState, ref possibleActions);
// iterate over each potential action, and add it to the open list.
// if the node was already seen before, then it is updated if the new cost is better than the old cost.
foreach (DefaultAction action in possibleActions)
{
float newg = x.g + action.cost;
if (stateMap.ContainsKey(action.state))
{
BestFirstSearchNode existingNode = stateMap[action.state];
// then, that means this node was seen before.
if (newg < existingNode.g)
{
// then, this means we need to update the node.
if (existingNode.alreadyExpanded == false)
{
openSet.Remove(existingNode);
}
stateMap.Remove(existingNode.action.state);
}
else
{
// otherwise, we don't bother adding this node... it already exists with a better cost.
continue;
}
}
DefaultAction nextAction = action;
float newf = domain.estimateTotalCost(ref action.state, ref idealGoalState, newg);
BestFirstSearchNode nextNode = new BestFirstSearchNode(newg, newf, ref x.action.state, ref nextAction);
stateMap[nextNode.action.state] = nextNode;
openSet.Add(nextNode);
}
}
if (openSet.Count == 0)
{
// if we get here, there was no solution.
actualStateReached = startState;
}
else
{
// if we get here, then we did not find a complete path.
// instead, just return whatever path we could construct.
// The idea is that if the user gave a reasonable heuristic,
// state space, and transitions, then the next node that
// would be expanded will be the most promising path anyway.
//
actualStateReached = (openSet.ElementAt(0)).action.state;
}
return(false); // returns false because plan is incomplete.
} //end _ComputePlan
public bool _computePlan(ref DefaultState startState, ref DefaultState idealGoalState, Dictionary <DefaultState, FringeSearchNode> Cache, ref DefaultState actualStateReached, float maxTime)
{
//Make sure Cache is empty when starting to compute plan
PlanningDomainBase domain = default(PlanningDomainBase);
float score = 0;
foreach (PlanningDomainBase d in _planningDomain)
{
if (d.evaluateDomain(ref startState) > score)
{
score = d.evaluateDomain(ref startState);
domain = d;
}
}
float newf = domain.estimateTotalCost(ref startState, ref idealGoalState, 0.0f);
FringeSearchNode rootNode = new FringeSearchNode(0.0f, newf, ref startState, ref startState);
rootNode.parent = null;
LinkedList <FringeSearchNode> fringe = new LinkedList <FringeSearchNode>();
fringe.AddFirst(rootNode);
foreach (KeyValuePair <DefaultState, FringeSearchNode> keyval in Cache)
{
if ((keyval.Key as FringePlanningState).state.Equals((startState as FringePlanningState).state))
{
Cache[keyval.Key] = rootNode;
break;
}
}
//flimit = h(start)
float flimit = rootNode.f - rootNode.g;
while (fringe.Count > 0)
{
float fmin = Mathf.Infinity;
LinkedListNode <FringeSearchNode> fringeNode = fringe.First;
while (fringeNode != null)
{
FringeSearchNode node = fringeNode.Value;
FringeSearchNode tempNode = default(FringeSearchNode);
foreach (DefaultState key in Cache.Keys)
{
if ((key as FringePlanningState).state.Equals((node.action.state as FringePlanningState).state))
{
tempNode = Cache[key]; break;
}
}
//FringeSearchNode tempNode = Cache[node.action.state];
if (tempNode.f > flimit)
{
fmin = Mathf.Min(tempNode.f, fmin);
fringeNode = fringeNode.Next;
continue;
}
if (domain.isAGoalState(ref tempNode.action.state, ref idealGoalState))
{
actualStateReached = tempNode.action.state;
return(true);
}
List <DefaultAction> possibleActions = new List <DefaultAction>();
possibleActions.Clear();
domain.generateTransitions(ref tempNode.action.state, ref tempNode.previousState, ref idealGoalState, ref possibleActions);
foreach (DefaultAction action in possibleActions)
{
float newg = tempNode.g + action.cost;
newf = domain.estimateTotalCost(ref action.state, ref idealGoalState, newg);
DefaultAction nextAction = action;
FringeSearchNode successor = new FringeSearchNode(newg, newf, ref tempNode.action.state, ref nextAction);
successor.parent = tempNode;
FringeSearchNode fn = default(FringeSearchNode);
bool exists = false;
foreach (KeyValuePair <DefaultState, FringeSearchNode> sn in Cache)
{
if ((sn.Key as FringePlanningState).state.Equals((successor.action.state as FringePlanningState).state))
{
if (sn.Value != null)
{
{ fn = sn.Value; exists = true; break; }
}
}
}
//if(Cache[successor.action.state] != null)
if (exists)
{
if (successor.g >= fn.g)
{
continue;
}
}
//If fringe contains successor
//if(fringe.Contains(successor))
// fringe.Remove(successor);
foreach (FringeSearchNode s in fringe)
{
if (s.action.state.Equals(successor.action.state))
{
fringe.Remove(s);
}
}
fringe.AddAfter(fringe.Find(node), successor);
//C[s]<-(gs, n) already added when node created
foreach (KeyValuePair <DefaultState, FringeSearchNode> sn in Cache)
{
if ((sn.Key as FringePlanningState).state.Equals((successor.action.state as FringePlanningState).state))
{
Cache[sn.Key] = successor; break;
}
}
//Cache[successor.action.state].g = newg;
//Cache[successor.action.state].parent = node;
}
fringeNode = fringeNode.Next;
fringe.Remove(tempNode);
}
flimit = fmin;
}
return(false);
}