private static IStringEvaluator combineTokens(List <IToken> tokens)
{
var valStack = new Stack <IStringEvaluator>();
var opeStack = new Stack <OperatorEvaluator>();
bool valueLasted = false;
Action <OperatorEvaluator> fnResolveOperator = (OperatorEvaluator ope) => {
ope.Right = valStack.Pop();
ope.Left = valStack.Pop();
valStack.Push(ope);
};
foreach (var token in tokens)
{
IStringEvaluator evaluator = token.getEvaluator();
if (evaluator is ValueEvaluator)
{
if (valueLasted)
{
throw new FormatException("Value expression duplicated.");
}
valStack.Push(evaluator);
valueLasted = true;
}
else if (evaluator is OperatorEvaluator)
{
OperatorEvaluator ope = (OperatorEvaluator)evaluator;
if (!valueLasted)
{
throw new FormatException("Operator expression duplicated.");
}
if (opeStack.Count > 0)
{
if (opeStack.Last().getPriority() <= ope.getPriority())
{
fnResolveOperator(opeStack.Pop());
}
}
opeStack.Push(ope);
valueLasted = false;
}
}
while (opeStack.Count > 0)
{
fnResolveOperator(opeStack.Pop());
}
if (valStack.Count == 0)
{
throw new FormatException("Operator expression is none.");
}
return(valStack.Last());
}
/// <summary>
/// Builds the operator decision tree for the evaluation of operators relevance in the SAS+ planning problem.
/// </summary>
/// <param name="operators">Operators of the SAS+ planning problem.</param>
/// <param name="variables">Variables data of the SAS+ planning problem.</param>
/// <returns>Operator decision tree of operators relevance.</returns>
public static IOperatorDecisionTreeNode BuildRelevanceTree(Operators operators, Variables variables)
{
OperatorEvaluator evaluator = (IOperator oper, int variable, out int value) => oper.GetEffects().IsVariableAffected(variable, out value);
return(BuildTree(new List <IOperator>(operators), GetAllDecisionVariables(variables), evaluator));
}
/// <summary>
/// Builds the operator decision tree from the given operators and decision variables.
/// </summary>
/// <param name="availableOperators">List of operators to be processed.</param>
/// <param name="decisionVariables">List of decision variables to be processed with their corresponding domain range.</param>
/// <param name="evaluator">Operator evaluator specifying how to handle operators during the tree building.</param>
/// <returns>Operator decision tree node corresponding to the input operators and decision variables.</returns>
private static IOperatorDecisionTreeNode BuildTree(List <IOperator> availableOperators, List <Tuple <int, int> > decisionVariables, OperatorEvaluator evaluator)
{
// if we have no remaining operators, then create an empty leaf node
if (availableOperators.Count == 0)
{
return(new OperatorDecisionTreeEmptyLeafNode());
}
// if we have no remaining decision variables, then create a leaf node containing the current operators list
if (decisionVariables.Count == 0)
{
return(new OperatorDecisionTreeLeafNode(availableOperators));
}
// find the current decision variable, i.e. available variable with the maximal domain range
int decisionVariableDomainRange = decisionVariables.Max(variable => variable.Item2);
int decisionVariable = decisionVariables.First(variable => variable.Item2 == decisionVariableDomainRange).Item1;
// prepare decision variables modifiers
Action removeCurrentDecisionVariable = () => { decisionVariables.RemoveAll(variable => variable.Item1 == decisionVariable); };
Action restoreCurrentDecisionVariable = () => { decisionVariables.Add(Tuple.Create(decisionVariable, decisionVariableDomainRange)); };
// prepare collections for sorting out available operators
List <IOperator>[] operatorsByValue = new List <IOperator> [decisionVariableDomainRange];
List <IOperator> nonAffectedOperators = new List <IOperator>();
for (int i = 0; i < operatorsByValue.Length; ++i)
{
operatorsByValue[i] = new List <IOperator>();
}
// sort out the available operators by the current decision variable: if the preconditions of the operator are constrained by the
// decision variable (applicability tree), or the decision variable is affected by the operator effects (relevance tree), then put
// it into the operatorsByValue collection, otherwise into the nonAffectedOperators collection
foreach (var oper in availableOperators)
{
int value;
if (evaluator(oper, decisionVariable, out value))
{
operatorsByValue[value].Add(oper);
}
else
{
nonAffectedOperators.Add(oper);
}
}
// the decision variable has zero impact -> continue without it
if (nonAffectedOperators.Count == availableOperators.Count)
{
removeCurrentDecisionVariable();
var result = BuildTree(nonAffectedOperators, decisionVariables, evaluator);
restoreCurrentDecisionVariable();
return(result);
}
// prepare a new decision node - create decision subtrees for all the possible values of the current decision variable
removeCurrentDecisionVariable();
IOperatorDecisionTreeNode[] childrenByValues = new IOperatorDecisionTreeNode[decisionVariableDomainRange];
for (int i = 0; i < decisionVariableDomainRange; ++i)
{
childrenByValues[i] = BuildTree(operatorsByValue[i], decisionVariables, evaluator);
}
IOperatorDecisionTreeNode childIndependentOnDecisionVariable = BuildTree(nonAffectedOperators, decisionVariables, evaluator);
restoreCurrentDecisionVariable();
// return the root of the current subtree
return(new OperatorDecisionTreeInnerNode(decisionVariable, childrenByValues, childIndependentOnDecisionVariable));
}
/// <summary>
/// Builds the operator decision tree for the evaluation of operators applicability in the SAS+ planning problem.
/// </summary>
/// <param name="operators">Operators of the SAS+ planning problem.</param>
/// <param name="variables">Variables data of the SAS+ planning problem.</param>
/// <returns>Operator decision tree of operators applicability.</returns>
public static IOperatorDecisionTreeNode BuildApplicabilityTree(Operators operators, Variables variables)
{
OperatorEvaluator evaluator = (IOperator oper, int variable, out int value) => oper.GetPreconditions().IsVariableConstrained(variable, out value);
return(BuildTree(new List <IOperator>(operators), GetAllDecisionVariables(variables), evaluator));
}