This chapter reviews measures of emergence, self-organization, complexity,homeostasis, and autopoiesis based on information theory. These measures arederived from proposed axioms and tested in two case studies: random Booleannetworks and an Arctic lake ecosystem.
Emergence is defined as the information a system or process produces.Self-organization is defined as the opposite of emergence, while complexity isdefined as the balance between emergence and self-organization. Homeostasisreflects the stability of a system. Autopoiesis is defined as the ratio betweenthe complexity of a system and the complexity of its environment. The proposedmeasures can be applied at different scales, which can be studied withmulti-scale profiles.
Via Bernard Ryefield