fmdpLearner.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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// =========================================================================
#ifndef GUM_FMDP_LEARNER_H
#define GUM_FMDP_LEARNER_H
// =========================================================================
// =========================================================================
#include <agrum/FMDP/learning/datastructure/imddi.h>
#include <agrum/FMDP/learning/datastructure/iti.h>
#include <agrum/FMDP/SDyna/Strategies/ILearningStrategy.h>
 
// =========================================================================
// =========================================================================
 
namespace gum {

 
  template < TESTNAME    VariableAttributeSelection,
             TESTNAME    RewardAttributeSelection,
             LEARNERNAME LearnerSelection >
  class FMDPLearner: public ILearningStrategy {
    using VariableLearnerType =
        typename LearnerSelect< LearnerSelection,
                                IMDDI< VariableAttributeSelection, false >,
                                ITI< VariableAttributeSelection, false > >::type;
 
    using RewardLearnerType = typename LearnerSelect< LearnerSelection,
                                                      IMDDI< RewardAttributeSelection, true >,
                                                      ITI< RewardAttributeSelection, true > >::type;
 
    using VarLearnerTable = HashTable< const DiscreteVariable*, VariableLearnerType* >;
 
    public:
    // ==========================================================================
    // ==========================================================================
 
    // ###################################################################
    // ###################################################################
    FMDPLearner(double learningThreshold, bool actionReward, double similarityThreshold = 0.05);
 
    // ###################################################################
    // ###################################################################
    ~FMDPLearner();

 
    // ###################################################################
    // ###################################################################
 
    public:
    // ==========================================================================
    // ==========================================================================
    void initialize(FMDP< double >* fmdp);
 
    // ==========================================================================
    // ==========================================================================
    MultiDimFunctionGraph< double >* _instantiateFunctionGraph_() {
      return _instantiateFunctionGraph_(Int2Type< LearnerSelection >());
    }
 
    MultiDimFunctionGraph< double >* _instantiateFunctionGraph_(Int2Type< IMDDILEARNER >) {
      return MultiDimFunctionGraph< double,
                                    ExactTerminalNodePolicy >::getReducedAndOrderedInstance();
    }
 
    MultiDimFunctionGraph< double >* _instantiateFunctionGraph_(Int2Type< ITILEARNER >) {
      return MultiDimFunctionGraph< double, ExactTerminalNodePolicy >::getTreeInstance();
    }
 
    // ==========================================================================
    // ==========================================================================
    VariableLearnerType* _instantiateVarLearner_(MultiDimFunctionGraph< double >* target,
                                                 gum::VariableSet&                mainVariables,
                                                 const DiscreteVariable*          learnedVar) {
      return _instantiateVarLearner_(target,
                                     mainVariables,
                                     learnedVar,
                                     Int2Type< LearnerSelection >());
    }
 
    VariableLearnerType* _instantiateVarLearner_(MultiDimFunctionGraph< double >* target,
                                                 gum::VariableSet&                mainVariables,
                                                 const DiscreteVariable*          learnedVar,
                                                 Int2Type< IMDDILEARNER >) {
      return new VariableLearnerType(target,
                                     _learningThreshold_,
                                     _similarityThreshold_,
                                     mainVariables,
                                     learnedVar);
    }
 
    VariableLearnerType* _instantiateVarLearner_(MultiDimFunctionGraph< double >* target,
                                                 gum::VariableSet&                mainVariables,
                                                 const DiscreteVariable*          learnedVar,
                                                 Int2Type< ITILEARNER >) {
      return new VariableLearnerType(target, _learningThreshold_, mainVariables, learnedVar);
    }
 
    // ==========================================================================
    // ==========================================================================
    RewardLearnerType* _instantiateRewardLearner_(MultiDimFunctionGraph< double >* target,
                                                  gum::VariableSet&                mainVariables) {
      return _instantiateRewardLearner_(target, mainVariables, Int2Type< LearnerSelection >());
    }
 
    RewardLearnerType* _instantiateRewardLearner_(MultiDimFunctionGraph< double >* target,
                                                  gum::VariableSet&                mainVariables,
                                                  Int2Type< IMDDILEARNER >) {
      return new RewardLearnerType(target,
                                   _learningThreshold_,
                                   _similarityThreshold_,
                                   mainVariables);
    }
 
    RewardLearnerType* _instantiateRewardLearner_(MultiDimFunctionGraph< double >* target,
                                                  gum::VariableSet&                mainVariables,
                                                  Int2Type< ITILEARNER >) {
      return new RewardLearnerType(target, _learningThreshold_, mainVariables);
    }

 
 
    // ###################################################################
    // ###################################################################
 
    public:
    // ==========================================================================
    // ==========================================================================
    bool addObservation(Idx actionId, const Observation* obs);
 
 
    // ==========================================================================
    // ==========================================================================
    void updateFMDP();

 
 
    // ###################################################################
    // ###################################################################
 
    public:
    // ==========================================================================
    // ==========================================================================
    Size size();
 
    // ==========================================================================
    // ==========================================================================
    const IVisitableGraphLearner* varLearner(Idx actionId, const DiscreteVariable* var) const {
      return _actionLearners_[actionId]->getWithDefault(var, nullptr);
    }
 
    virtual double rMax() const { return _rmax_; }
 
    private:
    double _rmax_;
 
    public:
    virtual double modaMax() const { return _modaMax_; }
 
    private:
    double _modaMax_;

 
 
    private:
    FMDP< double >* _fmdp_;
 
    HashTable< Idx, VarLearnerTable* > _actionLearners_;
 
    bool                                 _actionReward_;
    HashTable< Idx, RewardLearnerType* > _actionRewardLearners_;
    RewardLearnerType*                   _rewardLearner_;
 
    const double _learningThreshold_;
    const double _similarityThreshold_;
  };
 
 
} /* namespace gum */
 
#include <agrum/FMDP/learning/fmdpLearner_tpl.h>
 
#endif   // GUM_FMDP_LEARNER_H