Complexity science, as articulated by Daniel Schmachtenberger, is an interdisciplinary domain that examines systems with numerous interacting components, such as biological organisms, ecosystems, economies, and social structures. Schmachtenberger emphasizes that complexity science seeks to understand how intricate behaviors and patterns emerge from simple interactions and feedback loops within these systems. He underscores the importance of recognizing that traditional linear and reductionist approaches are often insufficient for grasping the intricate dynamics at play. By integrating insights from fields such as systems theory, network theory, and cybernetics, complexity science provides a richer, more holistic framework for addressing contemporary challenges that are inherently interconnected and multifaceted. Through this lens, Schmachtenberger advocates for a deeper appreciation of the adaptive, emergent, and often unpredictable nature of complex systems, ultimately fostering more resilient and effective strategies for navigating the complexities of the modern world.

See also: network dynamics, nonlinear dynamics, systems thinking, emergent property