adaptiveRMaxPlaner.h

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/**
 *
 *   Copyright 2005-2020 Pierre-Henri WUILLEMIN(@LIP6) & Christophe GONZALES(@AMU)
 *   info_at_agrum_dot_org
 *
 *  This library is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Lesser General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This library is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU Lesser General Public License for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with this library.  If not, see <http://www.gnu.org/licenses/>.
 *
 */


/**
 * @file
 * @brief Headers of the RMax planer class.
 *
 * @author Pierre-Henri WUILLEMIN(@LIP6) and Jean-Christophe MAGNAN and Christophe
 * GONZALES(@AMU)
 */

// =========================================================================
#ifndef GUM_ADAPTIVE_RMAX_PLANER_H
#define GUM_ADAPTIVE_RMAX_PLANER_H
// =========================================================================
#include <agrum/FMDP/SDyna/Strategies/IDecisionStrategy.h>
#include <agrum/FMDP/fmdp.h>
#include <agrum/FMDP/learning/fmdpLearner.h>
#include <agrum/FMDP/planning/structuredPlaner.h>
#include <agrum/FMDP/simulation/statesCounter.h>
// =========================================================================

namespace gum {

  /**
   * @class AdaptiveRMaxPlaner adaptiveRMaxPlaner.h
   * <agrum/FMDP/planning/adaptiveRMaxPlaner.h>
   * @brief A class to find optimal policy for a given FMDP.
   * @ingroup fmdp_group
   *
   * Perform a RMax planning on given in parameter factored markov decision
   * process
   *
   */
  class AdaptiveRMaxPlaner:
      public StructuredPlaner< double >,
      public IDecisionStrategy {
    // ###################################################################
    /// @name
    // ###################################################################
    /// @{
    public:
    // ==========================================================================
    ///
    // ==========================================================================
    static AdaptiveRMaxPlaner*
       ReducedAndOrderedInstance(const ILearningStrategy* learner,
                                 double                   discountFactor = 0.9,
                                 double                   epsilon        = 0.00001,
                                 bool                     verbose        = true) {
      return new AdaptiveRMaxPlaner(new MDDOperatorStrategy< double >(),
                                    discountFactor,
                                    epsilon,
                                    learner,
                                    verbose);
    }

    // ==========================================================================
    ///
    // ==========================================================================
    static AdaptiveRMaxPlaner* TreeInstance(const ILearningStrategy* learner,
                                            double discountFactor = 0.9,
                                            double epsilon        = 0.00001,
                                            bool   verbose        = true) {
      return new AdaptiveRMaxPlaner(new TreeOperatorStrategy< double >(),
                                    discountFactor,
                                    epsilon,
                                    learner,
                                    verbose);
    }

    /// @}

    // ###################################################################
    /// @name Constructor & destructor.
    // ###################################################################
    /// @{
    private:
    // ==========================================================================
    /// Default constructor
    // ==========================================================================
    AdaptiveRMaxPlaner(IOperatorStrategy< double >* opi,
                       double                       discountFactor,
                       double                       epsilon,
                       const ILearningStrategy*     learner,
                       bool                         verbose);

    // ==========================================================================
    /// Default destructor
    // ==========================================================================
    public:
    ~AdaptiveRMaxPlaner();

    /// @}


    // ###################################################################
    /// @name Planning Methods
    // ###################################################################
    /// @{

    public:
    // ==========================================================================
    /**
     * Initializes data structure needed for making the planning
     * @warning No calling this methods before starting the first makePlaninng
     * will surely and definitely result in a crash
     */
    // ==========================================================================
    void initialize(const FMDP< double >* fmdp);


    // ==========================================================================
    /**
     * Performs a value iteration
     *
     * @param nbStep : enables you to specify how many value iterations you wish
     * to do.
     * makePlanning will then stop whether when optimal value function is reach
     * or when nbStep have been performed
     */
    // ==========================================================================
    void makePlanning(Idx nbStep = 1000000);

    /// @}


    // ###################################################################
    /// @name Value Iteration Methods
    // ###################################################################
    /// @{

    protected:
    // ==========================================================================
    ///
    // ==========================================================================
    virtual void initVFunction_();

    // ==========================================================================
    /// Performs a single step of value iteration
    // ==========================================================================
    virtual MultiDimFunctionGraph< double >* valueIteration_();

    /// @}


    // ###################################################################
    /// @name Optimal policy extraction methods
    // ###################################################################
    /// @{

    protected:
    // ==========================================================================
    /// Perform the required tasks to extract an optimal policy
    // ==========================================================================
    virtual void evalPolicy_();

    /// @}

    private:
    void makeRMaxFunctionGraphs__();

    std::pair< NodeId, NodeId > visitLearner__(const IVisitableGraphLearner*,
                                               NodeId currentNodeId,
                                               MultiDimFunctionGraph< double >*,
                                               MultiDimFunctionGraph< double >*);
    void                        clearTables__();

    private:
    HashTable< Idx, MultiDimFunctionGraph< double >* > actionsRMaxTable__;
    HashTable< Idx, MultiDimFunctionGraph< double >* > actionsBoolTable__;
    const ILearningStrategy*                           fmdpLearner__;

    double rThreshold__;
    double rmax__;


    // ###################################################################
    /// @name Incremental methods
    // ###################################################################
    /// @{
    public:
    void checkState(const Instantiation& newState, Idx actionId) {
      if (!initializedTable__[actionId]) {
        counterTable__[actionId]->reset(newState);
        initializedTable__[actionId] = true;
      } else
        counterTable__[actionId]->incState(newState);
    }

    private:
    HashTable< Idx, StatesCounter* > counterTable__;
    HashTable< Idx, bool >           initializedTable__;

    bool initialized__;
    /// @}
  };

} /* namespace gum */

#endif   // GUM_ADAPTIVE_RMAX_PLANER_H