The transition from mathematical models to computational algorithms represents the next stage in the formal development of Vitology as an interdisciplinary scientific framework. While mathematical models provide formal representations of viability, computational algorithms enable their practical implementation through simulation, comparative analysis, prediction, optimization, and decision support. Despite significant advances in computational science, systems theory, artificial intelligence, and complex systems research, no unified algorithmic framework currently exists for analyzing viability as a universal organizational property across systems of different origins. This article proposes the conceptual foundations of computational algorithms for viability analysis within the framework of Vitology. Rather than presenting finalized software implementations, the study develops a methodological framework for constructing algorithms capable of analyzing multidimensional system states, evaluating developmental trajectories, identifying organizational regularities, and supporting computational investigation within the Space of Harmony. The proposed framework considers computational algorithms as scientific instruments that integrate mathematical models, quantitative indicators, empirical observations, and artificial intelligence into a unified computational methodology. Particular attention is devoted to algorithms for multidimensional state evaluation, trajectory analysis, pattern recognition, early detection of declining viability, comparative interdisciplinary analysis, and adaptive model refinement. Artificial intelligence is regarded as an essential methodological partner capable of accelerating computational analysis, discovering hidden multidimensional relationships, refining algorithmic performance, and supporting iterative scientific investigation while remaining subordinate to theoretical reasoning and empirical validation. The proposed approach establishes methodological foundations for the future development of computational platforms, predictive diagnostics, digital twins, intelligent decision-support systems, and interdisciplinary computational research devoted to understanding, preserving, restoring, and increasing the viability of complex natural, biological, ecological, social, organizational, technological, and artificial systems. Keywords Vitology, viability, computational algorithms, viability analysis, computational modeling, systems science, artificial intelligence, Space of Harmony, Harmony Navigation, multidimensional analysis, mathematical modeling, predictive diagnostics, decision support, empirical validation, interdisciplinary research.
Serhii Hostiunin (Sun,) studied this question.