GEGELATI
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Public Member Functions | List of all members
Selector::MapElites::DefaultDescriptors::ActionValues Class Reference

#include <mapElitesDefaultDescriptors.h>

Inheritance diagram for Selector::MapElites::DefaultDescriptors::ActionValues:
Selector::MapElites::MapElitesDescriptor

Public Member Functions

virtual void initDescriptor (const TPG::TPGGraph &graph, const Learn::LearningEnvironment &learningEnvironment) override
 Specialisation of initDescriptor.
 
virtual std::string getName () const override
 Specialisation of getName.
 
virtual void extractMetricsStep (std::vector< double > &metrics, const TPG::TPGVertex *agent, std::vector< double > actionValues, const Learn::LearningEnvironment &learningEnvironment) const override
 Specialisation of extractMetricsStep.
 
virtual void extractMetricsEpisode (std::vector< double > &metrics, const TPG::TPGVertex *agent, size_t nbStepsExecuted, const Learn::LearningEnvironment &learningEnvironment) const override
 Specialisation of extractMetricsEpisode.
 
- Public Member Functions inherited from Selector::MapElites::MapElitesDescriptor
virtual bool isInit () const
 method that return if the initDescriptor method has been executed
 
virtual std::pair< double, double > getMinAndMaxRange () const
 Get the min and max range of the descriptor.
 
virtual size_t getNbDescriptors () const
 Get the number of the descriptor.
 

Additional Inherited Members

- Protected Attributes inherited from Selector::MapElites::MapElitesDescriptor
size_t nbDescriptors
 Number of descriptor.
 
double minRange
 Minimum value in the archive.
 
double maxRange
 Maximum value in the archive.
 
bool init = false
 

Detailed Description

Class for ActionValues descriptor.

This descriptor is designed for continuous environments (an update could be made to be used on discrete environments too but it might not be useful).

It computes the average of the absolute of the action values over an episode.

Member Function Documentation

◆ extractMetricsEpisode()

void Selector::MapElites::DefaultDescriptors::ActionValues::extractMetricsEpisode ( std::vector< double > & metrics,
const TPG::TPGVertex * agent,
size_t nbStepsExecuted,
const Learn::LearningEnvironment & learningEnvironment ) const
overridevirtual

Specialisation of extractMetricsEpisode.

Reimplemented from Selector::MapElites::MapElitesDescriptor.

◆ extractMetricsStep()

void Selector::MapElites::DefaultDescriptors::ActionValues::extractMetricsStep ( std::vector< double > & metrics,
const TPG::TPGVertex * agent,
std::vector< double > actionValues,
const Learn::LearningEnvironment & learningEnvironment ) const
overridevirtual

Specialisation of extractMetricsStep.

Reimplemented from Selector::MapElites::MapElitesDescriptor.

◆ getName()

std::string Selector::MapElites::DefaultDescriptors::ActionValues::getName ( ) const
overridevirtual

Specialisation of getName.

Implements Selector::MapElites::MapElitesDescriptor.

◆ initDescriptor()

void Selector::MapElites::DefaultDescriptors::ActionValues::initDescriptor ( const TPG::TPGGraph & graph,
const Learn::LearningEnvironment & learningEnvironment )
overridevirtual

Specialisation of initDescriptor.

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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Implements Selector::MapElites::MapElitesDescriptor.


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