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GEGELATI
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Class to extract metrics from either the agent or the environment. More...
#include <mapElitesSelectionMetrics.h>
Public Member Functions | |
| MapElitesSelectionMetrics (std::vector< std::shared_ptr< const MapElitesDescriptor > > descriptors) | |
| Default constructor of MapEliteselectionMetrics with a vector of descriptors. | |
| MapElitesSelectionMetrics (double score, const std::map< std::shared_ptr< const MapElitesDescriptor >, std::vector< double > > &mapDescriptors) | |
| Constructor of MapEliteselectionMetrics with a vector of scores. | |
| MapElitesSelectionMetrics (double score) | |
| Constructor of MapEliteselectionMetrics with a vector of scores. | |
| const std::map< std::shared_ptr< const MapElitesDescriptor >, std::vector< double > > & | getMapDescriptors () const |
| Get a const ref to the scorePerClass attribute. | |
| void | initMetrics (const TPG::TPGVertex *agent, const Learn::LearningEnvironment &learningEnvironment) override |
| Specialization of the initialisation of the metrics. | |
| void | extractMetricsStep (const TPG::TPGVertex *agent, std::vector< double > actionValues, const Learn::LearningEnvironment &learningEnvironment) override |
| Specialization of the extraction of the metrics at the end of an episode. | |
| void | extractMetricsEpisode (const TPG::TPGVertex *agent, size_t nbStepsExecuted, const Learn::LearningEnvironment &learningEnvironment) override |
| Specialization of the extraction of the metrics at the end of an episode. | |
| virtual void | weightedSum (std::shared_ptr< SelectionMetrics > other, size_t nbEvaluation, size_t nbEvaluationOther) override |
| Specialization of weightedSum method to add the score per class and nbEvalPerClass. | |
Public Member Functions inherited from Selector::SelectionMetrics | |
| SelectionMetrics ()=default | |
| Default constructor. | |
| virtual | ~SelectionMetrics ()=default |
| Default destructor. | |
| SelectionMetrics (double score, double utility=0) | |
| Constructor with score and utility initialization. | |
| virtual double | getScore () const |
| virtual double | getUtility () const |
Protected Attributes | |
| std::map< std::shared_ptr< const MapElitesDescriptor >, std::vector< double > > | mapDescriptors |
| Map storing a descriptor and a Vector storing a double value per descriptor (i.e. per Action) of a classification LearningEnvironment. | |
Protected Attributes inherited from Selector::SelectionMetrics | |
| double | score = 0 |
| double | utility = 0 |
Additional Inherited Members | |
Static Public Member Functions inherited from Selector::SelectionMetrics | |
| template<class T > | |
| static T | weightedSum (T value, T valueOther, size_t nbEvaluation, size_t nbEvaluationOther) |
| Perform a weighted sum between 2 values. | |
Class to extract metrics from either the agent or the environment.
This metrics can be used to specify the selection of the selector. This class does not implement any metrics, it need to be override by the different selection methods.
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inline |
Default constructor of MapEliteselectionMetrics with a vector of descriptors.
| [in] | descriptors | the vector of descriptors to use. |
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inline |
Constructor of MapEliteselectionMetrics with a vector of scores.
| [in] | score | the score obtained by the agent. |
| [in] | mapDescriptors | the map of descriptors associated to their descriptor values. |
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inline |
Constructor of MapEliteselectionMetrics with a vector of scores.
| [in] | score | the score obtained by the agent. |
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overridevirtual |
Specialization of the extraction of the metrics at the end of an episode.
Reimplemented from Selector::SelectionMetrics.
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overridevirtual |
Specialization of the extraction of the metrics at the end of an episode.
Reimplemented from Selector::SelectionMetrics.
| const std::map< std::shared_ptr< const Selector::MapElites::MapElitesDescriptor >, std::vector< double > > & Selector::MapElites::MapElitesSelectionMetrics::getMapDescriptors | ( | ) | const |
Get a const ref to the scorePerClass attribute.
Copyright or © or Copr. IETR/INSA - Rennes (2025) :
Quentin Vacher qvach.nosp@m.er@i.nosp@m.nsa-r.nosp@m.enne.nosp@m.s.fr (2025)
GEGELATI is an open-source reinforcement learning framework for training artificial intelligence based on Tangled Program Graphs (TPGs).
This software is governed by the CeCILL-C license under French law and abiding by the rules of distribution of free software. You can use, modify and/ or redistribute the software under the terms of the CeCILL-C license as circulated by CEA, CNRS and INRIA at the following URL "http://www.cecill.info".
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overridevirtual |
Specialization of the initialisation of the metrics.
Reimplemented from Selector::SelectionMetrics.
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overridevirtual |
Specialization of weightedSum method to add the score per class and nbEvalPerClass.
Reimplemented from Selector::SelectionMetrics.