Systems Sciences and Nonlinear Intelligence Dynamics
What does the science of systems sciences and nonlinear intelligence dynamics constitute and what does it hold for future?
Systems sciences, as an interdisciplinary field, address the understanding of systems, from life at simple level to other interactions that become gradually complex across incredible spectra which range from mathematics to medicine, engineering, technology and science, spanning thru formal, natural, social, computational and applied sciences in order to develop transformative interdisciplinary foundations and merging them. Theories and applications along with the respective methodologies range within a variety of areas such as control theory, control systems, computational systems, social systems theory, systems biology, engineering, medicine, mathematics, exact sciences, natural sciences, system dynamics, physical laws, intelligence systems, robotic systems, service systems, computer science, systems engineering and systems psychology in complex systems, nonlinear systems, dynamical systems, chaotic systems, cybernetics, engineering theories, linguistics or systems theory, amongst the other ones. On the other hand, nonlinear intelligence dynamics, as a research field, serves to understand and realize multiple layers of intelligence with nonlinear intelligent dynamics of a system being a thought-provoking vital subject matter owing to the entailment of system-of-systems considerations to peruse research and practice at different levels with different goals. Accordingly, the capabilities of predictability, estimation, interpretation, relying on the scope from mathematical sciences, computer sciences to applied sciences as well as engineering mathematics with nonlinear intelligence dynamics lie at the intersection with various fields which are characterized by complex, chaotic, transient, nonlinear and dynamic components in order to reveal the significance of optimized approaches in real-world systems and related realms. As for future directions, significant advancements in critical points and perspectives, with mathematical modeling grounded in the integration of systems science and nonlinear intelligence dynamics, aim at paving the way for the future research toward the formulation, design, deployment, simulation, analysis and multicriteria-based optimization besides the extension of the predictability horizons of applicable optimal solutions to problems emerging as formidable challenges in the ever-evolving and fast-changing global landscape. Across this line of thought, the integrated solutions with the dynamic approach can support critical multistage decision-making processes through the lenses of realistic, actionable and timely information oriented towards the solution of problems in a tailored and to-the-point manner in systems sciences.
—Yeliz Karaca, President
Systems Sciences and Nonlinear Intelligence Dynamics
(SSNID) Institute Academy
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