/Users/fpy/titan-1-5-MBARI/Mers/Estimation/Discrete/ApproximateBeliefState/BSEObjectiveFunction.cpp

00001 
00002 //
00003 // Copyright (c) 2005           Model-based Embedded and Robotic Systems Group
00004 // All Rights Reserved          Massachusetts Institute of Technology
00005 //
00006 // This software is provided as is. Model-based Embedded and Robotic Systems
00007 // (MERS) group does not assume any responsibility.
00008 //
00009 // Organization:                        Model-based Embedded and Robotic Systems Group
00010 //                                                      Massachusetts Institute of Technology
00011 //
00013 
00014 #include "BSEObjectiveFunction.h"
00015 
00016 #ifdef _MSC_VER
00017 #pragma warning( disable : 4786 )
00018 #endif
00019 
00020 #include <Mers/Estimation/Discrete/Trajectories.h>
00021 #include <Mers/Estimation/Discrete/Estimate.h>
00022 
00023 #include <Mers/Generators/BFIG/BFIGAssignment.h>
00024 #include <Mers/Generators/BFIG/BFIGVariable.h>
00025 #include <Mers/Models/Base/BaseModelVariableArray.h>
00026 #include <Mers/Models/Base/BaseModelVariable.h>
00027 #include <Mers/Models/Base/BaseModelValue.h>
00028 #include <Mers/Models/Base/BaseModelAssignment.h>
00029 #include <Mers/Models/Base/BaseModelAssignmentArray.h>
00030 
00031 using namespace Mers::Estimation::Discrete::ApproximateBeliefState;
00032 using Mers::Estimation::Discrete::Trajectories;
00033 using Mers::Estimation::Discrete::Estimate;
00034 using Mers::Generators::BFIG::BFIGAssignment;
00035 using Mers::Generators::BFIG::BFIGVariable;
00036 using Mers::Models::Base::BaseModelVariableArray;
00037 using Mers::Models::Base::BaseModelVariable;
00038 using Mers::Models::Base::BaseModelValue;
00039 using Mers::Models::Base::BaseModelAssignment;
00040 using Mers::Models::Base::BaseModelAssignmentArray;
00041 using std::vector;
00042 using std::map;
00043 using std::pair;
00044 using std::cout;
00045 using std::endl;
00046 
00048 //      CONSTRUCTOR
00050 
00051 BSEObjectiveFunction::BSEObjectiveFunction(BaseModelVariableArray const * dVs,
00052                 const map<unsigned int,unsigned int> pMap, vector<double> allTransProbs, map<unsigned int,double> sProbs)
00053 : MEObjectiveFunction(dVs, pMap, allTransProbs, sProbs)
00054 {}
00055 
00057 
00058 BSEObjectiveFunction::~BSEObjectiveFunction()
00059 {
00060 }
00061 
00062 
00064 //      PUBLIC METHODS
00066 
00067 
00068 
00069 
00071 //      PROTECTED METHODS
00073 
00074 double 
00075 BSEObjectiveFunction::calculateUtility(vector<BaseModelAssignment const *> & bmAssignments,
00076                                                                            int sourceStateIndex) const
00077 {
00078         (void) sourceStateIndex; // Not used by BSEObjectiveFunction
00079 
00080         double fX = 0.0;
00081         double trajectoryProb = 1.0;
00082         unsigned int i, j, varUID;
00083         unsigned int numSourceStates = (unsigned int) sourceStateProbabilities.size();
00084 
00085         unsigned int numNotAssigned = 0;
00086         unsigned int numAssigned = 0;
00087 
00088         map<unsigned int, bool> wasAssigned;
00089         map<unsigned int, unsigned int> assignedValue;
00090         for(i=0; i<decisionVariables->getLength(); i++)
00091                 wasAssigned[(*decisionVariables)[i]->getUID()] = false;
00092 
00093         for(i=0; i<bmAssignments.size(); i++)
00094         {
00095                 varUID = bmAssignments[i]->getVariable()->getUID();
00096                 wasAssigned[varUID] = true;
00097                 assignedValue[varUID] = bmAssignments[i]->getValue()->getUID();                 // Assumes probabilities are still listed in UID order
00098         }
00099 
00100         for(i=0; i<numSourceStates; i++)
00101         {
00102                 map<unsigned int, double>::const_iterator sProbItr = sourceStateProbabilities.find(i);
00103                 trajectoryProb = (*sProbItr).second;    // Direct access isn't a constant function so apparently this is required
00104                 for(j=0; j<decisionVariables->getLength(); j++)
00105                 {
00106                         varUID = (*decisionVariables)[j]->getUID();
00107                         if(wasAssigned[varUID])
00108                         {
00109                                 map<unsigned int, unsigned int>::const_iterator pMapItr = probabilityMap.find(varUID);
00110                                 trajectoryProb *= allTransitionProbabilitiesForAllStates[i*(allTransitionProbabilitiesForAllStates.size() / 
00111                                                 numSourceStates) + (*pMapItr).second + assignedValue[varUID]];
00112                                 numAssigned++;
00113                         }
00114                         else
00115                         {
00116                                 map<pair<unsigned int, unsigned int>, double>::const_iterator opItr;
00117                                 opItr = optimisticProbabilities.find(pair<unsigned int, unsigned int>(varUID, i));
00118                                 trajectoryProb *= (*opItr).second;
00119                                 numNotAssigned++;
00120                         }
00121                 }
00122                 fX += trajectoryProb;
00123         }
00124 
00125 //      cout << "# assigned: " << numAssigned << ", # not assigned: " << numNotAssigned << ", prob: " << fX << endl;
00126 
00127         return fX;
00128 }
00129 
00131 //      PRIVATE METHODS
00133 
00134 
00135 double 
00136 BSEObjectiveFunction::calculatePropagationUtility(vector<BaseModelAssignment const *> & bmAssignments,
00137                                                                                                   int sourceStateIndex) const
00138 {
00139         return BSEObjectiveFunction::calculateUtility(bmAssignments, sourceStateIndex);
00140 }
00141 
00143 

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