01277nas a2200157   4500008004100000245009900041210006900140260001300209300001000222520076000232100002300992700002201015700002301037700002401060856003501084       2014                        eng d00aInformation Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis0 aInformation Measures of Complexity Emergence Selforganization Ho  bSpringer  a19-513 a<p>This chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization. Homeostasis reflects the stability of a system. Autopoiesis is defined as the ratio between the complexity of a system and the complexity of its environment. The proposed measures can be applied at different scales, which can be studied with multi-scale profiles.</p>
1 aFernández, Nelson1 aMaldonado, Carlos1 aGershenson, Carlos1 aProkopenko, Mikhail  uhttp://arxiv.org/abs/1304.1842