public IncrementalPruningStd(PomdpStd pomdp, double delta) {
startTimer();
initValueIteration(pomdp);
this.delta = delta;
bmdp = new BeliefMdpStd(pomdp);
current = new ValueFunctionStd(pomdp.nrStates());
current.push(new AlphaVector(bmdp.nrStates()));
registerInitTime();
}
public IterationStats iterate() {
startTimer();
old = current;
ValueIterationStats iterationStats = (ValueIterationStats) this.iterationStats;
current = new ValueFunctionStd(bmdp.nrStates());
for (int a = 0; a < bmdp.nrActions(); a++) {
// Perform Projections
ArrayList<ValueFunctionStd> psi = new ArrayList<ValueFunctionStd>();
for (int o = 0; o < bmdp.nrObservations(); o++) {
ValueFunctionStd proj = new ValueFunctionStd(bmdp.nrStates());
for (int idx = 0; idx < old.size(); idx++) {
AlphaVector alpha = old.getAlphaVector(idx);
AlphaVector res = bmdp.projection(alpha, a, o);
proj.push(res);
}
iterationStats.registerLp(proj.prune(delta));
psi.add(proj);
}
ValueFunctionStd rewFunc = bmdp.getRewardValueFunction(a);
// rewFunc.scale(1.0/(double)bmdp.nrObservations());
psi.add(rewFunc);
// Now Cross sum...
while (psi.size() > 1) {
ValueFunctionStd vfA = psi.remove(0);
ValueFunctionStd vfB = psi.remove(0);
vfA.crossSum(vfB);
iterationStats.registerLp(vfA.prune(delta));
psi.add(vfA);
}
ValueFunctionStd vfA = psi.remove(0);
current.merge(vfA);
}
iterationStats.registerLp(current.prune(delta));
System.out.println(current.size());
registerValueIterationStats();
return iterationStats;
}