vector<double> BeliefValue::GetValues(const BeliefSet &Beliefs,
const QFunctionsDiscrete &Q)
{
vector<double> values(Beliefs.size()),
maxValues(Beliefs.size(),-DBL_MAX);
for(QFDcit i=Q.begin();i!=Q.end();++i)
{
values=GetValues(Beliefs,*i);
for(unsigned int j=0;j!=values.size();++j)
if(values[j]>maxValues[j])
maxValues[j]=values[j];
}
return(maxValues);
}
void AlphaVectorPlanning::ExportBeliefSet(const BeliefSet &B,
const string &filename)
{
ofstream fp(filename.c_str());
if(!fp)
{
cerr << "AlphaVectorPlanning::ExportBeliefSet: failed to open file "
<< filename << endl;
}
int nrB=B.size();
for(int b=0;b!=nrB;b++)
{
for(unsigned int s=0;s!=B[b]->Size();s++)
fp << B[b]->Get(s) << " ";
fp << endl;
}
}
/**
* Implements equation (3.5) of PhD thesis Matthijs.
*/
vector<double> BeliefValue::GetValues(const BeliefSet &Beliefs,
const ValueFunctionPOMDPDiscrete &V)
{
int nrInV=V.size();
int nrB=Beliefs.size();
vector<double> values(nrB,-DBL_MAX);
double x;
for(int b=0;b!=nrB;b++)
for(int i=0;i!=nrInV;i++)
{
// compute inner product of belief with vector
x=Beliefs[b]->InnerProduct(V[i].GetValues());
// keep the maximizing value
if(x>values[b])
values[b]=x;
}
return(values);
}
