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

Abstract

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.

Keywords

• hierarchical coevolutionary algorithm
• multi-criteria optimization under conflict and uncertainty
• distributed computing
• containerization
• orchestration