public List <RandomVariable> forward_backward(List <String> perceptions)
{
RandomVariable[] forwardMessages = new RandomVariable[perceptions
.Count + 1];
RandomVariable backwardMessage = priorDistribution.createUnitBelief();
RandomVariable[] smoothedBeliefs = new RandomVariable[perceptions
.Count + 1];
forwardMessages[0] = priorDistribution;
smoothedBeliefs[0] = null;
// populate forward messages
for (int i = 0; i < perceptions.Count; i++)
{ // N.B i starts at 1,
// not zero
forwardMessages[i + 1] = forward(forwardMessages[i], perceptions[i]);
}
for (int i = perceptions.Count; i > 0; i--)
{
RandomVariable smoothed = priorDistribution.duplicate();
smoothed.updateFrom(forwardMessages[i].asMatrix().arrayTimes(
backwardMessage.asMatrix()));
smoothed.normalize();
smoothedBeliefs[i] = smoothed;
backwardMessage = calculate_next_backward_message(
forwardMessages[i], backwardMessage, perceptions[i - 1]);
}
return(new List <RandomVariable>(smoothedBeliefs));
}
