Neuro-Evolutionary Synthesis of Game Models of Control under Uncertainty Based on Distributed Computing Technology

The methodology basic principles of the neuro-evolutionary synthesis of multi-object multi-criteria systems control models under conflict and uncertainty in real time are discussed. The proposed methodology includes the following main stages: a hierarchical optimization game model under conflict and...

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Published inEngineering proceedings Vol. 33; no. 1; p. 59
Main Authors Vladimir A. Serov, Daria L. Popova, Pavel P. Rogalev, Anastasia V. Tararina
Format Journal Article
LanguageEnglish
Published MDPI AG 01.07.2023
Subjects
containerization
distributed computing
hierarchical coevolutionary algorithm
multi-criteria optimization under conflict and uncertainty
orchestration
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ISSN2673-4591
DOI10.3390/engproc2023033059

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Summary:The methodology basic principles of the neuro-evolutionary synthesis of multi-object multi-criteria systems control models under conflict and uncertainty in real time are discussed. The proposed methodology includes the following main stages: a hierarchical optimization game model under conflict and uncertainty development; a library development of hierarchical coevolutionary algorithms for multi-criteria optimization under conflict and uncertainty; software implementation of hierarchical coevolutionary algorithms library based on distributed computing technology; and game algorithms of control under uncertainty synthesis based on the technology of neural networks ensembles.
ISSN:2673-4591
DOI:10.3390/engproc2023033059