/****************************************************************************
 *   This file is part of the aGrUM/pyAgrum library.                        *
 *                                                                          *
 *   Copyright (c) 2005-2026 by                                             *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *                                                                          *
 *   The aGrUM/pyAgrum library is free software; you can redistribute it    *
 *   and/or modify it under the terms of either :                           *
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 *    - 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,                              *
 *    - the MIT license (MIT),                                              *
 *    - or both in dual license, as here.                                   *
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 *   (see https://agrum.gitlab.io/articles/dual-licenses-lgplv3mit.html)    *
 *                                                                          *
 *   This aGrUM/pyAgrum library is distributed in the hope that it will be  *
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 *   See LICENCES for more details.                                         *
 *                                                                          *
 *   SPDX-FileCopyrightText: Copyright 2005-2026                            *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *   SPDX-License-Identifier: LGPL-3.0-or-later OR MIT                      *
 *                                                                          *
 *   Contact  : info_at_agrum_dot_org                                       *
 *   homepage : http://agrum.gitlab.io                                      *
 *   gitlab   : https://gitlab.com/agrumery/agrum                           *
 *                                                                          *
 ****************************************************************************/

#pragma once


/** @file
 * @brief The local search learning algorithm (for directed graphs)
 *
 * @author Christophe GONZALES(_at_AMU) and Pierre-Henri WUILLEMIN(_at_LIP6)
 */
#include <agrum/BN/learning/localSearchWithTabuList.h>   // to ease IDE parser
#ifndef DOXYGEN_SHOULD_SKIP_THIS

namespace gum {

  namespace learning {

    /// default constructor
    INLINE LocalSearchWithTabuList::LocalSearchWithTabuList() {
      disableEpsilon();
      disableMinEpsilonRate();
      disableMaxIter();
      disableMaxTime();
      GUM_CONSTRUCTOR(LocalSearchWithTabuList);
    }

    /// copy constructor
    INLINE LocalSearchWithTabuList::LocalSearchWithTabuList(const LocalSearchWithTabuList& from) :
        ApproximationScheme(from), _MaxNbDecreasing_(from._MaxNbDecreasing_) {
      GUM_CONS_CPY(LocalSearchWithTabuList);
    }

    /// move constructor
    INLINE LocalSearchWithTabuList::LocalSearchWithTabuList(LocalSearchWithTabuList&& from) :
        ApproximationScheme(std::move(from)), _MaxNbDecreasing_(std::move(from._MaxNbDecreasing_)) {
      GUM_CONS_MOV(LocalSearchWithTabuList);
    }

    /// destructor
    INLINE LocalSearchWithTabuList::~LocalSearchWithTabuList() {
      GUM_DESTRUCTOR(LocalSearchWithTabuList);
    }

    /// copy operator
    INLINE LocalSearchWithTabuList&
        LocalSearchWithTabuList::operator=(const LocalSearchWithTabuList& from) = default;

    /// move operator
    INLINE LocalSearchWithTabuList&
        LocalSearchWithTabuList::operator=(LocalSearchWithTabuList&& from) {
      ApproximationScheme::operator=(std::move(from));
      _MaxNbDecreasing_ = std::move(from._MaxNbDecreasing_);
      return *this;
    }

    /// set the max number of changes decreasing the score that we allow to
    /// apply
    INLINE void LocalSearchWithTabuList::setMaxNbDecreasingChanges(Size nb) {
      _MaxNbDecreasing_ = nb;
    }

    /// returns the approximation policy of the learning algorithm
    INLINE ApproximationScheme& LocalSearchWithTabuList::approximationScheme() { return *this; }

  } /* namespace learning */

} /* namespace gum */

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
