private double CalculateMaximumProbabilityOfCid(AutoResizeBigVector <double> cache, PrecalculatedTransitionTarget[] precalculatedTransitionTargets, double[] stateProbabilities, long currentCid)
{
if (cache != null && HasCacheEntry(cache, currentCid))
{
return(cache[(int)currentCid]);
}
var result = double.NaN;
LabeledTransitionMarkovDecisionProcess.ContinuationGraphElement cge = Ltmdp.GetContinuationGraphElement(currentCid);
if (cge.IsChoiceTypeUnsplitOrFinal)
{
var transitionTargetPosition = cge.To;
var transitionTarget = Ltmdp.GetTransitionTarget(transitionTargetPosition);
if (precalculatedTransitionTargets[transitionTargetPosition].HasFlag(PrecalculatedTransitionTarget.Satisfied))
{
result = 1.0;
}
else if (precalculatedTransitionTargets[transitionTargetPosition].HasFlag(PrecalculatedTransitionTarget.Excluded))
{
result = 0.0;
}
else
{
result = stateProbabilities[transitionTarget.TargetState];
}
}
else
{
if (cge.IsChoiceTypeForward)
{
// Note, cgi.Probability is used in the branch "else if (cge.IsChoiceTypeProbabilitstic)"
result = CalculateMaximumProbabilityOfCid(cache, precalculatedTransitionTargets, stateProbabilities, cge.From);
}
if (cge.IsChoiceTypeNondeterministic)
{
var biggest = double.NegativeInfinity;
for (var i = cge.From; i <= cge.To; i++)
{
var resultOfChild = CalculateMaximumProbabilityOfCid(cache, precalculatedTransitionTargets, stateProbabilities, i);
if (resultOfChild > biggest)
{
biggest = resultOfChild;
}
}
result = biggest;
}
else if (cge.IsChoiceTypeProbabilitstic)
{
var sum = 0.0;
for (var i = cge.From; i <= cge.To; i++)
{
var transitionProbability = Ltmdp.GetContinuationGraphElement(i).Probability;
var resultOfChild = CalculateMaximumProbabilityOfCid(cache, precalculatedTransitionTargets, stateProbabilities, i);
sum += transitionProbability * resultOfChild;
}
result = sum;
}
}
if (cache != null)
{
cache[(int)currentCid] = result;
}
return(result);
}
private static void ExportCid(LabeledTransitionMarkovDecisionProcess ltmdp, TextWriter sb, string fromNode, bool fromProbabilistic, long currentCid)
{
LabeledTransitionMarkovDecisionProcess.ContinuationGraphElement choice = ltmdp.GetContinuationGraphElement(currentCid);
if (choice.IsChoiceTypeUnsplitOrFinal)
{
var thisNode = $"cid{currentCid}";
sb.WriteLine($" {thisNode} [ shape=point,width=0.1,height=0.1,label=\"\" ];");
if (fromProbabilistic)
{
sb.WriteLine($" {fromNode}->{thisNode} [ arrowhead =\"onormal\", label=\"{choice.Probability.ToString(CultureInfo.InvariantCulture)}\"];");
}
else
{
sb.WriteLine($" {fromNode}->{thisNode} [ arrowhead =\"normal\"];");
}
var transitionTarget = ltmdp.GetTransitionTarget(choice.To);
sb.Write($" {thisNode} -> {transitionTarget.TargetState} [ arrowhead =\"normal\",");
sb.Write("label=\"");
for (int i = 0; i < ltmdp.StateFormulaLabels.Length; i++)
{
if (i > 0)
{
sb.Write(",");
}
if (transitionTarget.Formulas[i])
{
sb.Write("t");
}
else
{
sb.Write("f");
}
}
sb.WriteLine("\"];");
}
else if (choice.IsChoiceTypeForward)
{
// only forward node (no recursion)
// do not print thisNode
var toNode = $"cid{choice.To}";
sb.WriteLine($" {fromNode}->{toNode} [ style =\"dashed\", label=\"{choice.Probability.ToString(CultureInfo.InvariantCulture)}\"];");
}
else
{
// we print how we came to this node
var thisNode = $"cid{currentCid}";
sb.WriteLine($" {thisNode} [ shape=point,width=0.1,height=0.1,label=\"\" ];");
if (fromProbabilistic)
{
sb.WriteLine($" {fromNode}->{thisNode} [ arrowhead =\"onormal\", label=\"{choice.Probability.ToString(CultureInfo.InvariantCulture)}\"];");
}
else
{
sb.WriteLine($" {fromNode}->{thisNode} [ arrowhead =\"normal\"];");
}
for (var i = choice.From; i <= choice.To; i++)
{
ExportCid(ltmdp, sb, thisNode, choice.IsChoiceTypeProbabilitstic, i);
}
}
}
