GEGELATI
Public Member Functions | Protected Attributes | List of all members
Learn::Job Class Reference

This class embeds roots for the simulations. More...

#include <job.h>

Inheritance diagram for Learn::Job:
Learn::AdversarialJob

Public Member Functions

 Job ()=delete
 Deleted default constructor.
 
 Job (const TPG::TPGVertex *root, uint64_t archiveSeed=0, uint64_t idx=0)
 Constructor enabling storing elements in the job so that the Learning Agents will be able to use them later. More...
 
virtual ~Job ()=default
 Default virtual destructor.
 
uint64_t getIdx () const
 Getter of index. More...
 
uint64_t getArchiveSeed () const
 Getter of archiveSeed. More...
 
virtual const TPG::TPGVertexgetRoot () const
 Getter of the root. More...
 

Protected Attributes

const TPG::TPGVertexroot
 
const uint64_t idx
 
const uint64_t archiveSeed
 

Detailed Description

This class embeds roots for the simulations.

The goal of the Job is to contain one root, so that each job will match with one simulation/evaluation. A basic learning agent will embed one root per job to do as many simulations as there are roots.

Constructor & Destructor Documentation

◆ Job()

Learn::Job::Job ( const TPG::TPGVertex root,
uint64_t  archiveSeed = 0,
uint64_t  idx = 0 
)
inline

Constructor enabling storing elements in the job so that the Learning Agents will be able to use them later.

Parameters
[in]rootThe root that will be encapsulated into the job.
[in]archiveSeedThe archive seed that will be used with this job.
[in]idxThe index of this job.

Member Function Documentation

◆ getArchiveSeed()

uint64_t Learn::Job::getArchiveSeed ( ) const

Getter of archiveSeed.

Returns
The archive seed of the job.

◆ getIdx()

uint64_t Learn::Job::getIdx ( ) const

Getter of index.

Returns
The index of the job.

Copyright or © or Copr. IETR/INSA - Rennes (2019 - 2020) :

Karol Desnos kdesn.nosp@m.os@i.nosp@m.nsa-r.nosp@m.enne.nosp@m.s.fr (2019 - 2020) Pierre-Yves Le Rolland-Raumer plero.nosp@m.lla@.nosp@m.insa-.nosp@m.renn.nosp@m.es.fr (2020)

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".

As a counterpart to the access to the source code and rights to copy, modify and redistribute granted by the license, users are provided only with a limited warranty and the software's author, the holder of the economic rights, and the successive licensors have only limited liability.

In this respect, the user's attention is drawn to the risks associated with loading, using, modifying and/or developing or reproducing the software by the user in light of its specific status of free software, that may mean that it is complicated to manipulate, and that also therefore means that it is reserved for developers and experienced professionals having in-depth computer knowledge. Users are therefore encouraged to load and test the software's suitability as regards their requirements in conditions enabling the security of their systems and/or data to be ensured and, more generally, to use and operate it in the same conditions as regards security.

The fact that you are presently reading this means that you have had knowledge of the CeCILL-C license and that you accept its terms.

◆ getRoot()

const TPG::TPGVertex * Learn::Job::getRoot ( ) const
virtual

Getter of the root.

Returns
The root embedded by the job.

Reimplemented in Learn::AdversarialJob.

Member Data Documentation

◆ archiveSeed

const uint64_t Learn::Job::archiveSeed
protected

Seed that will be used to randomize archive.

◆ idx

const uint64_t Learn::Job::idx
protected

Index associated to this job.

◆ root

const TPG::TPGVertex* Learn::Job::root
protected

The root contained in the job.


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