1. Emergence: Complex systems exhibit properties that arise from interactions among components, which cannot be deduced simply by examining individual parts.

2. Nonlinearity: Small changes can have disproportionate effects due to feedback loops and intricate interdependencies.

3. Self-Organization: Systems often develop order spontaneously through internal dynamics without centralized control.

4. Adaptation and Co-evolution: Components and systems adjust in response to environmental changes, highlighting a process of mutual influence and evolution.

5. Interdisciplinary Perspective: Complexity theory transcends traditional disciplinary boundaries, encouraging holistic and integrative approaches to understanding systems.

A prime example is in economics: models predicting market behavior can influence investor actions, thereby altering the market’s dynamics and validating—or invalidating—the original predictions. In this sense, the model becomes part of the system it seeks to describe. Another instance is found in social systems where public policies, based on theoretical models, shape individual behavior; as people adjust their actions in response, they modify the very context the models attempt to capture. These cases demonstrate the reflexivity and self-referentiality inherent in complex systems, where boundaries between the model and its subject blur.