Genetic Algorithms and Evolutionary Strategies in Modern Computational Linguistics: Navigating the Uncertainty, Turbulence, and Systemic Risks of the SHIVA Concept

Abstract

In the conditions of high uncertainty and transformation of the modern digital environment (“SHIVA world”), traditional methods of natural language processing lose their effectiveness. The article is devoted to the application of genetic algorithms and evolutionary strategies for optimizing language models under conditions of high uncertainty (“SHIVA world”). The paper analyzes their role in text processing, annotating language corpora, and automatic selection of neural network architectures. The authors prove that the ability of evolutionary computing to self-adapt allows creating effective hybrid platforms for digital philology.