internal double CalculateMaximumFinalProbability(AutoResizeBigVector <double> cache, double[] initialStateProbabilities)
{
var cid = Nmdp.GetRootContinuationGraphLocationOfInitialState();
cache?.Clear(cid); //use cid as offset, because it is the smallest element
return(CalculateMaximumProbabilityOfCid(cache, initialStateProbabilities, cid));
}
public double CalculateMinimumFinalProbability(AutoResizeBigVector <double> cache, PrecalculatedTransitionTarget[] precalculatedTransitionTargets, double[] initialStateProbabilities)
{
var cid = Ltmdp.GetRootContinuationGraphLocationOfInitialState();
cache?.Clear(cid); //use cid as offset, because it is the smallest element
return(CalculateMinimumProbabilityOfCid(cache, precalculatedTransitionTargets, initialStateProbabilities, cid));
}
private void Clear(long cidRoot)
{
_probabilityOfCid.Clear(cidRoot); // use cidRoot as offset, because it is the smallest element
_continuationGraphLeafOfCid.Clear(cidRoot);
_probabilityOfCid[cidRoot] = 1.0;
_ltmdpContinuationDistributionMapper.Clear();
}
internal double[] MaximumIterator(AutoResizeBigVector <double> cache, Dictionary <int, bool> exactlyOneStates, Dictionary <int, bool> exactlyZeroStates, int steps)
{
var stopwatch = new Stopwatch();
stopwatch.Start();
var stateCount = Nmdp.States;
var xold = new double[stateCount];
var xnew = CreateDerivedVector(exactlyOneStates);
var loops = 0;
while (loops < steps)
{
// switch xold and xnew
var xtemp = xold;
xold = xnew;
xnew = xtemp;
loops++;
for (var i = 0; i < stateCount; i++)
{
if (exactlyOneStates.ContainsKey(i))
{
//we could remove this line, because already set by CreateDerivedVector and never changed when we initialize xold with CreateDerivedVector(directlySatisfiedStates)
xnew[i] = 1.0;
}
else if (exactlyZeroStates.ContainsKey(i))
{
//we could remove this line, because already set by CreateDerivedVector and never changed when we initialize xold with CreateDerivedVector(directlySatisfiedStates)
xnew[i] = 0.0;
}
else
{
var cid = Nmdp.GetRootContinuationGraphLocationOfState(i);
cache?.Clear(cid); //use cid as offset, because it is the smallest element
xnew[i] = CalculateMaximumProbabilityOfCid(cache, xold, cid);
}
}
if (loops % 10 == 0)
{
stopwatch.Stop();
var currentProbability = CalculateMaximumFinalProbability(cache, xnew);
_output?.WriteLine(
$"{loops} Bounded Until iterations in {stopwatch.Elapsed}. Current probability={currentProbability.ToString(CultureInfo.InvariantCulture)}");
stopwatch.Start();
}
}
stopwatch.Stop();
return(xnew);
}
internal double[] MaximumIterator(AutoResizeBigVector <double> cache, PrecalculatedTransitionTarget[] precalculatedTransitionTargets, int steps)
{
var stopwatch = new Stopwatch();
stopwatch.Start();
var stateCount = Ltmdp.SourceStates.Count;
var xold = new double[stateCount];
var xnew = new double[stateCount];
var loops = 0;
while (loops < steps)
{
// switch xold and xnew
var xtemp = xold;
xold = xnew;
xnew = xtemp;
loops++;
for (var i = 0; i < stateCount; i++)
{
var cid = Ltmdp.GetRootContinuationGraphLocationOfState(i);
cache?.Clear(cid); //use cid as offset, because it is the smallest element
xnew[i] = CalculateMaximumProbabilityOfCid(cache, precalculatedTransitionTargets, xold, cid);
}
if (loops % 10 == 0)
{
stopwatch.Stop();
var currentProbability = CalculateMaximumFinalProbability(cache, precalculatedTransitionTargets, xnew);
_output?.WriteLine(
$"{loops} Bounded Until iterations in {stopwatch.Elapsed}. Current probability={currentProbability.ToString(CultureInfo.InvariantCulture)}");
stopwatch.Start();
}
}
stopwatch.Stop();
return(xnew);
}