General Systems Theory
Developed by Ludwig von Bertalanffy in the mid-20th century, GST proposes that systems share common principles regardless of their constituent elements or domain, emphasizing wholeness over reductionism.
An interdisciplinary framework studying complex systems across scientific, social, and organizational domains. Explore foundational concepts, cybernetics, emergent behaviors, and modern applications in AI, ecology, and governance.
Developed by Ludwig von Bertalanffy in the mid-20th century, GST proposes that systems share common principles regardless of their constituent elements or domain, emphasizing wholeness over reductionism.
The study of regulatory systems in animals, machines, and organizations. Explores homeostatic mechanisms, negative/positive feedback, and Norbert Wiener's foundational contributions to information theory.
Networks of agents that adapt and self-organize through local interactions. Covers biological ecosystems, markets, immune systems, and AI-driven multi-agent environments.
A holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time within the context of larger systems. Includes causal loop diagrams and stock-flow models.
Expands classical cybernetics by including the observer within the system. Explores recursive observation, epistemological shifts, and contributions by Heinz von Foerster and Humberto Maturana.
Application of systems concepts to business and institutional structures. Covers open systems theory, contingency models, and stakeholder interdependence in modern corporate governance.
Hermann Haken's theory of cooperative effects in multi-component systems. Examines how order parameters emerge from chaotic fluctuations and govern macroscopic behavior in lasers, fluids, and social dynamics.
Bronfenbrenner's framework for understanding human development as shaped by nested environmental systems. Expanded into modern socio-ecological models addressing climate resilience and biodiversity networks.
Mechanisms of physiological stability vs. dynamic adaptation to stress. Explores feedback regulation, predictive homeostasis, and their relevance to systems biology and psychiatric research.