Compară metode

	Criticitate auto-organizată	Modelarea bazată pe agenți (ABM)
Domeniu	Sisteme complexe	Simulare
Familie	Regression model	Process / pipeline
Anul apariției	1987	1970s–1990s (formalized as a field)
Autorul original	Per Bak, Chao Tang & Kurt Wiesenfeld	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Tip	Dynamical systems model	Computational simulation method
Sursa seminală	Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of 1/f noise. Physical Review Letters, 59(4), 381–384.	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Denumiri alternative	SOC, Sandpile Model, Critical Self-Organization, Kendiliğinden Örgütlenen Kritiklik	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Înrudite	3	5
Rezumat	Self-Organized Criticality (SOC) is a dynamical systems framework introduced by Per Bak, Chao Tang, and Kurt Wiesenfeld in 1987 to explain how large, dissipative systems spontaneously evolve toward a critical state without external fine-tuning. At the critical state, the system produces scale-invariant fluctuations — avalanches whose size and duration follow power-law distributions — and generates 1/f (pink) noise in its power spectrum.	Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone.