01262nas a2200133   4500008004100000245010700041210006900148300001000217490000700227520080700234100002301041700002301064856004101087       2012                        eng d00aComplexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales0 aComplexity and Information Measuring Emergence Selforganization   a29-440 v183 aConcepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales.1 aGershenson, Carlos1 aFernández, Nelson  uhttp://dx.doi.org/10.1002/cplx.21424