Implements the CMSA. More...

#include <shark/Algorithms/DirectSearch/CMSA.h>

Inheritance diagram for shark::CMSA:

Public Member Functions
	CMSA (random::rng_type &rng=random::globalRng)
	Default c'tor.

std::string	name () const
	From INameable: return the class name.

SHARK_EXPORT_SYMBOL void	read (InArchive &archive)
	Read the component from the supplied archive.

SHARK_EXPORT_SYMBOL void	write (OutArchive &archive) const
	Write the component to the supplied archive.

SHARK_EXPORT_SYMBOL void	init (ObjectiveFunctionType const &function, SearchPointType const &p)
	Initializes the algorithm for the supplied objective function.

SHARK_EXPORT_SYMBOL void	init (ObjectiveFunctionType const &function, SearchPointType const &initialSearchPoint, std::size_t lambda, std::size_t mu, double initialSigma, const boost::optional< RealMatrix > &initialCovarianceMatrix=boost::optional< RealMatrix >())
	Initializes the algorithm for the supplied objective function.

SHARK_EXPORT_SYMBOL void	step (ObjectiveFunctionType const &function)
	Executes one iteration of the algorithm.

void	setInitialSigma (double initSigma)
	sets the initial step length sigma

void	setMu (std::size_t mu)
	Sets the number of selected samples.

void	setLambda (std::size_t lambda)
	Sets the number of sampled points.

std::size_t	mu () const
	Accesses the size of the parent population.

std::size_t	lambda () const
	Accesses the size of the offspring population.

RealVector	eigenValues () const

double	sigma () const

Public Member Functions inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
std::size_t	numInitPoints () const
	By default most single objective optimizers only require a single point.

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)
	Initialize the optimizer for the supplied objective function using a set of initialisation points.

virtual const SolutionType &	solution () const
	returns the current solution of the optimizer

Public Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
const Features &	features () const

virtual void	updateFeatures ()

bool	requiresValue () const

bool	requiresFirstDerivative () const

bool	requiresSecondDerivative () const

bool	canSolveConstrained () const

bool	requiresClosestFeasible () const

virtual	~AbstractOptimizer ()

virtual void	init (ObjectiveFunctionType const &function)
	Initialize the optimizer for the supplied objective function.

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)=0
	Initialize the optimizer for the supplied objective function using a set of initialisation points.

virtual void	step (ObjectiveFunctionType const &function)=0
	Carry out one step of the optimizer for the supplied objective function.

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor.

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...).

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...).

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Types
typedef Individual< RealVector, double, LightChromosome >	IndividualType
	The type of individual used by the CMSA.

Protected Member Functions
SHARK_EXPORT_SYMBOL std::vector< IndividualType >	generateOffspring () const
	Samples lambda individuals from the search distribution

SHARK_EXPORT_SYMBOL void	updatePopulation (std::vector< IndividualType > const &offspring)
	Updates the strategy parameters based on the supplied offspring population.

SHARK_EXPORT_SYMBOL void	doInit (std::vector< SearchPointType > const &points, std::vector< ResultType > const &functionValues, std::size_t lambda, std::size_t mu, double initialSigma)
	Initializes the internal data structures of the CMSA.

Protected Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
void	checkFeatures (ObjectiveFunctionType const &objectiveFunction)
	Convenience function that checks whether the features of the supplied objective function match with the required features of the optimizer.

Additional Inherited Members
Public Types inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
typedef base_type::SearchPointType	SearchPointType

typedef base_type::SolutionType	SolutionType

typedef base_type::ResultType	ResultType

typedef base_type::ObjectiveFunctionType	ObjectiveFunctionType

Public Types inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
enum	Feature { REQUIRES_VALUE = 1 , REQUIRES_FIRST_DERIVATIVE = 2 , REQUIRES_SECOND_DERIVATIVE = 4 , CAN_SOLVE_CONSTRAINED = 8 , REQUIRES_CLOSEST_FEASIBLE = 16 }
	Models features that the optimizer requires from the objective function. More...

typedef PointType	SearchPointType

typedef ResultT	ResultType

typedef SolutionTypeT	SolutionType

typedef AbstractObjectiveFunction< PointType, ResultType >	ObjectiveFunctionType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Protected Attributes inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
SolutionType	m_best
	Current solution of the optimizer.

Protected Attributes inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
Features	m_features

Detailed Description

Implements the CMSA.

The algorithm is described in

H. G. Beyer, B. Sendhoff (2008). Covariance Matrix Adaptation Revisited: The CMSA Evolution Strategy In Proceedings of the Tenth International Conference on Parallel Problem Solving from Nature (PPSN X), pp. 123-132, LNCS, Springer-Verlag

Definition at line 63 of file CMSA.h.

Member Typedef Documentation

◆ IndividualType

typedef Individual< RealVector, double, LightChromosome > shark::CMSA::IndividualType

protected

The type of individual used by the CMSA.

Definition at line 147 of file CMSA.h.

Constructor & Destructor Documentation

◆ CMSA()

shark::CMSA::CMSA ( random::rng_type & rng = random::globalRng )

inline

Default c'tor.

Definition at line 74 of file CMSA.h.

References shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::m_features, and shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::REQUIRES_VALUE.

Member Function Documentation

◆ doInit()

SHARK_EXPORT_SYMBOL void shark::CMSA::doInit	(	std::vector< SearchPointType > const &	points,
		std::vector< ResultType > const &	functionValues,
		std::size_t	lambda,
		std::size_t	mu,
		double	initialSigma
	)

protected

Initializes the internal data structures of the CMSA.

◆ eigenValues()

RealVector shark::CMSA::eigenValues ( ) const

inline

Definition at line 138 of file CMSA.h.

References shark::MultiVariateNormalDistributionCholesky::lowerCholeskyFactor(), and shark::sqr().

◆ generateOffspring()

SHARK_EXPORT_SYMBOL std::vector< IndividualType > shark::CMSA::generateOffspring ( ) const

protected

Samples lambda individuals from the search distribution

◆ init() [1/2]

SHARK_EXPORT_SYMBOL void shark::CMSA::init	(	ObjectiveFunctionType const &	function,
		SearchPointType const &	initialSearchPoint,
		std::size_t	lambda,
		std::size_t	mu,
		double	initialSigma,
		const boost::optional< RealMatrix > &	initialCovarianceMatrix = `boost::optional< RealMatrix >()`
	)

Initializes the algorithm for the supplied objective function.

◆ init() [2/2]

SHARK_EXPORT_SYMBOL void shark::CMSA::init	(	ObjectiveFunctionType const &	function,
		SearchPointType const &	p
	)

virtual

Initializes the algorithm for the supplied objective function.

Implements shark::AbstractSingleObjectiveOptimizer< RealVector >.

◆ lambda()

std::size_t shark::CMSA::lambda ( ) const

inline

Accesses the size of the offspring population.

Definition at line 134 of file CMSA.h.

Referenced by setLambda().

◆ mu()

std::size_t shark::CMSA::mu ( ) const

inline

Accesses the size of the parent population.

Definition at line 129 of file CMSA.h.

Referenced by setMu().

◆ name()

std::string shark::CMSA::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 85 of file CMSA.h.

◆ read()

SHARK_EXPORT_SYMBOL void shark::CMSA::read ( InArchive & archive )

virtual

Read the component from the supplied archive.

Parameters

[in,out] archive The archive to read from.

Reimplemented from shark::ISerializable.

◆ setInitialSigma()

void shark::CMSA::setInitialSigma ( double initSigma )

inline

sets the initial step length sigma

It is by default <=0 which means that sigma =1/sqrt(numVariables)

Definition at line 114 of file CMSA.h.

◆ setLambda()

void shark::CMSA::setLambda ( std::size_t lambda )

inline

Sets the number of sampled points.

Definition at line 124 of file CMSA.h.

References lambda().

◆ setMu()

void shark::CMSA::setMu ( std::size_t mu )

inline

Sets the number of selected samples.

Definition at line 119 of file CMSA.h.

References mu().

◆ sigma()

double shark::CMSA::sigma ( ) const

inline

Definition at line 142 of file CMSA.h.

◆ step()

SHARK_EXPORT_SYMBOL void shark::CMSA::step ( ObjectiveFunctionType const & function )

Executes one iteration of the algorithm.

◆ updatePopulation()

SHARK_EXPORT_SYMBOL void shark::CMSA::updatePopulation ( std::vector< IndividualType > const & offspring )

protected

Updates the strategy parameters based on the supplied offspring population.

◆ write()

SHARK_EXPORT_SYMBOL void shark::CMSA::write ( OutArchive & archive ) const

virtual

Write the component to the supplied archive.

Parameters

[in,out] archive The archive to write to.

Reimplemented from shark::ISerializable.

The documentation for this class was generated from the following file:

include/shark/Algorithms/DirectSearch/CMSA.h

Public Member Functions

Protected Types

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ IndividualType

Constructor & Destructor Documentation

◆ CMSA()

Member Function Documentation

◆ doInit()

◆ eigenValues()

◆ generateOffspring()

◆ init() [1/2]

◆ init() [2/2]

◆ lambda()

◆ mu()

◆ name()

◆ read()

◆ setInitialSigma()

◆ setLambda()

◆ setMu()

◆ sigma()

◆ step()

◆ updatePopulation()

◆ write()