Resumen
- The study of complex systems is an interdisciplinary field [1 p. 4]; however, sciences of complexity remain under common and general principles [2], such as micro and macro level manifold [3, p. 41], emergency and chaos [4], interactions among a large number of agents [5], environment and aggregation [6], interdependencies [7], propagation, nonlinearity, feedback loops, open systems, memory and history, adaptation and self-regulation. Existing models are: a) autopoiesis (reproduction, replication, and ontogeny of structural change), b) dynamic systems (large-scale modeling, nonlinearity and unexpected behavior), c) dissipative systems (conditions far from equilibrium and triggering events), and d) dynamics of chaos (cumulative and chaotic nature of changes, moving away from equilibrium) [2]. Thus, complexity consists of a number of theories [8] and not a unified method and insight [9]; it is an intriguing concept with no characterization agreed on, and discussions are about intuitive notions [10]. Although metaphorical language is one of the existing approaches to complexity [11] and many models could have complex properties [4], concepts need to be properly understood, translating them into a useful model of reality [12], and caution is required, when trying to model a system as complex.