#include <GLearnerLib.h>

Inheritance diagram for GClasses::MyRecurrentModel:

Public Member Functions
	MyRecurrentModel (GSupervisedLearner pTransition, GSupervisedLearner pObservation, size_t actionDims, size_t contextDims, size_t obsDims, GRand pRand, std::vector< size_t > pParamDims, const char *stateFilename, double validateInterval)

virtual	~MyRecurrentModel ()

virtual void	onFinishedComputingStateEstimate (GMatrix *pStateEstimate)
	This method is called when trainMoses finishes computing the state estimate. By default, it does nothing, but you can overload it if you wish to do something with it. More...

virtual void	onObtainValidationScore (int timeSlice, double seconds, double squaredError)

Public Member Functions inherited from GClasses::GRecurrentModel
	GRecurrentModel (GSupervisedLearner pTransition, GSupervisedLearner pObservation, size_t actionDims, size_t contextDims, size_t obsDims, GRand pRand, std::vector< size_t > pParamDims=NULL)
	Takes ownership of pTransition and pObservation. More...

	GRecurrentModel (GDomNode pNode, GRand pRand)
	Load from a DOM. More...

virtual	~GRecurrentModel ()

virtual void	calibrate (const double *pObs)
	See the comment for GSystemLearner::calibrate. More...

double *	context ()
	Returns a pointer to the context vector. More...

size_t	contextDims ()
	Returns the number of dimensions in the context (state) vector. More...

virtual void	doAction (const double *pAction)
	See the comment for GSystemLearner::doAction. More...

GImage *	frames (GMatrix pDataAction, GMatrix pDataObs, bool calibrateContext, unsigned int frameWidth, int stepsPerImage, double scalePredictions)
	Generates a film-strip-like sequence of frames that compare the expected observations (left) with predicted observations (right). If the predictions are not in the form of images, or they are not parameterized with two variables, then this method will throw. More...

size_t	obsDims ()
	Returns the number of obs dims. More...

GSupervisedLearner *	observationFunc ()
	Returns the observation function. More...

virtual void	onObtainValidationScore (size_t timeSlice, double seconds, double squaredError)
	If validateDuringTraining was called, then this method is called whenever validation data is obtained. More...

size_t	paramDims ()
	Trains with the back-prop-through-time algorithm. Returns the final sequence length. More...

size_t *	paramRanges ()

double *	params ()

virtual void	predict (double *pObs)
	See the comment for GSystemLearner::predict. More...

void	predictPixel (const double pParams, double pObs)

double	quickValidate (GMatrix pDataAction, GMatrix pDataObs, size_t pixelSamples, double *paramArray, bool monotonic)
	Quickly compute an error estimate for use as an optimization heurisitic. More...

virtual GDomNode *	serialize (GDom *pDoc) const
	See the comment for GSystemLearner::serialize. More...

void	setTrainingSeconds (double d)
	Set the number of seconds to train. More...

void	setUseIsomap (bool b)
	Specify whether to use Isomap (instead of BreadthFirstUnfolding). (This only applies when trainMoses is called.) More...

void	trainEvolutionary (GMatrix pActions, GMatrix pObservations)
	Trains with an evolutionary optimizer. More...

void	trainHillClimber (GMatrix pActions, GMatrix pObservations, double dev, double decay, double seconds, bool climb, bool anneal)
	Trains with a hill climber. More...

void	trainMoses (GMatrix pActions, GMatrix pObservations)
	Trains with the MOSES algorithm. (Calls onFinishedComputingStateEstimate when the state estimate is computed.) More...

GSupervisedLearner *	transitionFunc ()
	Returns the transition function. More...

double	validate (std::vector< GMatrix * > &validationData, bool calibrateContext, bool monotonic, double multiplier)
	Computes the mean squared error with respect to some test sequence of actions and observations. More...

void	validateDuringTraining (double timeInterval, std::vector< GMatrix * > *pValidationData)
	Perform validation at periodic intervals with the specified data during training. Results are passed to the onObtainValidationScore method. pValidationData should refer to some number of validation data pairs, where each validation data pair is an observation dataset followed by an action dataset. More...

Public Member Functions inherited from GClasses::GSystemLearner
	GSystemLearner ()

	GSystemLearner (GDomNode *pNode)

virtual	~GSystemLearner ()

Protected Attributes
double	m_dStart

const char *	m_stateFilename

double	m_validateInterval

Protected Attributes inherited from GClasses::GRecurrentModel
size_t	m_actionDims

size_t	m_channels

size_t	m_contextDims

double	m_multiplier

size_t	m_obsDims

size_t	m_paramDims

double *	m_pBuf

double *	m_pContext

size_t	m_pixels

GSupervisedLearner *	m_pObservationFunc

size_t *	m_pParamRanges

double *	m_pParams

GRand *	m_pRand

GSupervisedLearner *	m_pTransitionFunc

std::vector< GMatrix * > *	m_pValidationData

double	m_trainingSeconds

bool	m_transitionDelta

bool	m_useIsomap

double	m_validationInterval

Additional Inherited Members
Static Public Member Functions inherited from GClasses::GRecurrentModel
static void	blurImageVector (const double pIn, double pOut, int wid, int hgt, int chan, double valueRange, int radius, int iters)
	Blur the image vector. More...

Protected Member Functions inherited from GClasses::GRecurrentModel
GMatrix *	joshuaEstimateState (GMatrix pActions, GMatrix pObservations)

GMatrix *	mosesEstimateState (GMatrix pActions, GMatrix pObservations)

void	prepareForOptimization (GMatrix pActions, GMatrix pObservations)

void	trainObservationFunction (GMatrix pEstState, GMatrix pObservations)

void	trainObservationFunctionIteratively (double dStart, GMatrix pEstState, GMatrix pObservations)

void	trainTransitionFunction (GMatrix pActions, GMatrix pEstState)

Protected Member Functions inherited from GClasses::GSystemLearner
GDomNode *	baseDomNode (GDom pDoc, const char szClassName) const
	Child classes should use this in their implementation of serialize. More...

Constructor & Destructor Documentation

GClasses::MyRecurrentModel::MyRecurrentModel	(	GSupervisedLearner *	pTransition,
		GSupervisedLearner *	pObservation,
		size_t	actionDims,
		size_t	contextDims,
		size_t	obsDims,
		GRand *	pRand,
		std::vector< size_t > *	pParamDims,
		const char *	stateFilename,
		double	validateInterval
	)

inline

virtual GClasses::MyRecurrentModel::~MyRecurrentModel ( )

inlinevirtual

Member Function Documentation

virtual void GClasses::MyRecurrentModel::onFinishedComputingStateEstimate ( GMatrix * pStateEstimate )

inlinevirtual

This method is called when trainMoses finishes computing the state estimate. By default, it does nothing, but you can overload it if you wish to do something with it.

Reimplemented from GClasses::GRecurrentModel.

virtual void GClasses::MyRecurrentModel::onObtainValidationScore	(	int	timeSlice,
		double	seconds,
		double	squaredError
	)

inlinevirtual

Member Data Documentation

double GClasses::MyRecurrentModel::m_dStart

protected

const char* GClasses::MyRecurrentModel::m_stateFilename

protected

double GClasses::MyRecurrentModel::m_validateInterval

protected

Public Member Functions

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation