* New tree configuration of the project:
.../
... + -- EO
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+-- src ----- + -- EDO
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+-- test + -- MO
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+-- tutorial + -- MOEO
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+-- doc + -- SMP
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... + -- EOMPI
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+ -- EOSERIAL
Question for current maintainers: ./README: new release?
Also:
* Moving out eompi & eoserial modules (issue #2).
* Correction of the errors when executing "make doc" command.
* Adding a solution for the conflicting headers problem (see the two CMake Cache
Values: PROJECT_TAG & PROJECT_HRS_INSTALL_SUBPATH) (issue #1)
* Header inclusions:
** src: changing absolute paths into relative paths ('#include <...>' -> '#include "..."')
** test, tutorial: changing relative paths into absolute paths ('#include "..."' -> '#include <...>')
* Moving out some scripts from EDO -> to the root
* Add a new script for compilation and installation (see build_gcc_linux_install)
* Compilation with uBLAS library or EDO module: now ok
* Minor modifications on README & INSTALL files
* Comment eompi failed tests with no end
*** TODO: CPack (debian (DEB) & RedHat (RPM) packages) (issues #6 & #7) ***
This commit is contained in:
Adèle Harrissart
parent
515bd5943d
commit
490e837f7a
2359 changed files with 7688 additions and 16329 deletions
211
src/edo/edoAlgoAdaptive.h
Executable file
211
src/edo/edoAlgoAdaptive.h
Executable file
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/*
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The Evolving Distribution Objects framework (EDO) is a template-based,
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ANSI-C++ evolutionary computation library which helps you to write your
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own estimation of distribution algorithms.
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2.1 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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Copyright (C) 2010 Thales group
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*/
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/*
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Authors:
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Johann Dréo <johann.dreo@thalesgroup.com>
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Pierre Savéant <pierre.saveant@thalesgroup.com>
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*/
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#ifndef _edoAlgoAdaptive_h
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#define _edoAlgoAdaptive_h
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#include "../eo/utils/eoRNG.h"
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#include "edoAlgo.h"
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#include "edoEstimator.h"
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#include "edoModifierMass.h"
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#include "edoSampler.h"
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#include "edoContinue.h"
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/** A generic stochastic search template for algorithms that need a distribution parameter.
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*
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* An adaptive algorithm will directly updates a distribution, it must thus be instanciated
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* with an edoDistrib at hand. Thus, this distribution object should be instanciated appart.
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* The reference to this distribution is generally also needed by at least one of the
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* algorithm's operator, generally for algorithms that shares the same algorithms across
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* operators and/or iterations.
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*
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* If you no operator needs to update the distribution, then it is simpler to use an
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* edoAlgoStateless .
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*
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* @ingroup Algorithms
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*/
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template < typename D >
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class edoAlgoAdaptive : public edoAlgo< D >
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{
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public:
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//! Alias for the type EOT
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typedef typename D::EOType EOType;
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//! Alias for the atom type
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typedef typename EOType::AtomType AtomType;
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//! Alias for the fitness
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typedef typename EOType::Fitness Fitness;
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public:
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/*!
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Takes algo operators, all are mandatory
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\param distrib A distribution to use, if you want to update this parameter (e.gMA-ES) instead of replacing it (e.g. an EDA)
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\param evaluator Evaluate a population
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\param selector Selection of the best candidate solutions in the population
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\param estimator Estimation of the distribution parameters
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\param sampler Generate feasible solutions using the distribution
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\param replacor Replace old solutions by new ones
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\param pop_continuator Stopping criterion based on the population features
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\param distribution_continuator Stopping criterion based on the distribution features
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*/
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edoAlgoAdaptive(
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D & distrib,
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eoPopEvalFunc < EOType > & evaluator,
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eoSelect< EOType > & selector,
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edoEstimator< D > & estimator,
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edoSampler< D > & sampler,
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eoReplacement< EOType > & replacor,
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eoContinue< EOType > & pop_continuator,
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edoContinue< D > & distribution_continuator
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) :
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_distrib(distrib),
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_evaluator(evaluator),
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_selector(selector),
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_estimator(estimator),
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_sampler(sampler),
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_replacor(replacor),
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_pop_continuator(pop_continuator),
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_dummy_continue(),
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_distribution_continuator(distribution_continuator)
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{}
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//! constructor without an edoContinue
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/*!
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Takes algo operators, all are mandatory
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\param distrib A distribution to use, if you want to update this parameter (e.gMA-ES) instead of replacing it (e.g. an EDA)
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\param evaluator Evaluate a population
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\param selector Selection of the best candidate solutions in the population
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\param estimator Estimation of the distribution parameters
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\param sampler Generate feasible solutions using the distribution
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\param replacor Replace old solutions by new ones
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\param pop_continuator Stopping criterion based on the population features
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*/
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edoAlgoAdaptive (
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D & distrib,
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eoPopEvalFunc < EOType > & evaluator,
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eoSelect< EOType > & selector,
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edoEstimator< D > & estimator,
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edoSampler< D > & sampler,
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eoReplacement< EOType > & replacor,
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eoContinue< EOType > & pop_continuator
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) :
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_distrib( distrib ),
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_evaluator(evaluator),
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_selector(selector),
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_estimator(estimator),
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_sampler(sampler),
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_replacor(replacor),
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_pop_continuator(pop_continuator),
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_dummy_continue(),
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_distribution_continuator( _dummy_continue )
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{}
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/** Call the algorithm
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*
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* \param pop the population of candidate solutions
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* \return void
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*/
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void operator ()(eoPop< EOType > & pop)
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{
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assert(pop.size() > 0);
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eoPop< EOType > current_pop;
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eoPop< EOType > selected_pop;
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// update the extern distribution passed to the estimator (cf. CMA-ES)
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// OR replace the dummy distribution for estimators that do not need extern distributions (cf. EDA)
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_distrib = _estimator(pop);
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// Evaluating a first time the candidate solutions
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// The first pop is not supposed to be evaluated (@see eoPopLoopEval).
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// _evaluator( current_pop, pop );
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do {
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// (1) Selection of the best points in the population
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_selector(pop, selected_pop);
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assert( selected_pop.size() > 0 );
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// (2) Estimation of the distribution parameters
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_distrib = _estimator(selected_pop);
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// (3) sampling
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// The sampler produces feasible solutions (@see edoSampler that
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// encapsulate an edoBounder)
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current_pop.clear();
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for( unsigned int i = 0; i < pop.size(); ++i ) {
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current_pop.push_back( _sampler(_distrib) );
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}
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// (4) Evaluate new solutions
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_evaluator( pop, current_pop );
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// (5) Replace old solutions by new ones
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_replacor(pop, current_pop); // e.g. copy current_pop in pop
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} while( _distribution_continuator( _distrib ) && _pop_continuator( pop ) );
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} // operator()
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protected:
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//! The distribution that you want to update
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D & _distrib;
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//! A full evaluation function.
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eoPopEvalFunc<EOType> & _evaluator;
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//! A EOType selector
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eoSelect<EOType> & _selector;
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//! A EOType estimator. It is going to estimate distribution parameters.
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edoEstimator<D> & _estimator;
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//! A D sampler
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edoSampler<D> & _sampler;
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//! A EOType replacor
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eoReplacement<EOType> & _replacor;
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//! A EOType population continuator
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eoContinue<EOType> & _pop_continuator;
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//! A D continuator that always return true
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edoDummyContinue<D> _dummy_continue;
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//! A D continuator
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edoContinue<D> & _distribution_continuator;
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};
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#endif // !_edoAlgoAdaptive_h
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