Information and Self-Organization

Abstract

The process of "self-organization" takes place in open and complex systems that acquire spatio-temporal or functional structures without specific ordering instructions from the outside. In domains such as physics, chemistry or biology, the phrase, "far from equilibrium", refers to systems that are "far from thermal equilibrium", while in other disciplines, the term refers to the property of being "away from the resting state". Such systems are "complex" in the sense that they are composed of many interacting components, parts, elements, etc., and "open" in the sense that they exchange with their environment matter, energy, and information. Here, "information" may imply Shannon information [1], as a measure of the capacity of a channel through which a message passes, pragmatic information, as the impact of a message on recipients, or semantic information, as the meaning conveyed by a message.An attempt to bring these lines of thought together was made by Hermann Haken in his 1988 book Information and Self-Organization [2]. In the meantime, a number of authors have studied the interplay between information and self-organization in a variety of fields. Though the selection of the relevant authors and topics is surely not complete, we believe that this special issue mirrors the state of these interdisciplinary approaches fairly well. In fact, the various papers of this Special Issue expose the different ways processes of self-organization are linked with the various forms of information. As will be seen below, a study of such links has consequences on a number of research domains, ranging from physics and chemistry, through the life sciences and cognitive science, including human behavior and action, to our understanding of society, economics, and the dynamics of cities and urbanization.As will be seen below, the contributions to this Special Issue shed light on the various facets of information and self-organization. And since these various facets do not lend themselves to a topic-oriented order, and since a reader may prefer one over another, we present the papers in an alphabetic order that follows the family name of the first author of each article. The ContributionsA central theme in the theories of complexity is the self-organized bottom-up transition from the local micro-scale of a system's elementary parts to the global macro-scale of the system as a whole. In a way, the various theories of complexity differ in their conceptualization of this scale-dependent transition. Harald Atmanspacher [3] approaches this issue from the perspective of his notions of contextual emergence and the associated process of partitioning; both notions are related to the property that complex systems are open in the sense that they exchange matter, energy and information with

Evolutionary potential games on lattices

“…The crucial problem of extending the maximum entropy principle to non-physical systems lies in the adequate choice of constraints. This approach is used successfully in the analysis of complex [124] and chaotic systems.…”

“…Counterexamples are systems with long-range interactions or systems on some types of small-world networks where we cannot apply the traditional methods directly. In the wide field of statistical physics there are some new directions and approaches to describe the macroscopic behavior of the mentioned systems when considering complex [124], or other dynamical systems [128,129], and those non-equilibrium systems that behave like the superpositions of the Boltzmann distributions [130,131]. Surveying the latter directions goes beyond the scope of the present work, our attention will be focused on the description of phenomena occurring in large spatial systems.…”

From Learning to Consciousness: An Example Using Expected Float Entropy Minimisation

“…Shannon entropy is notably used in recent theories of consciousness and self-organization; see [ 10 , 11 ]. The definition of float entropy (see Definition 5) has some similarity to that of Boltzmann’s entropy where the entropy of a macrostate is proportional to the log of the number of microstates satisfying the macrostate.…”

Information Characteristics, Processes, and Mechanisms of Self‐Organization Evolution

“…In addition, it is also worth mentioning the work of the founder of synergetics, Haken, who is still very diligent in thinking and writing, despite his advanced age. In recent years, he has published several articles: "Self-organisation and information in biosystems: a case study [8]," " Water Freeman and Some oughts on Brain Dynamics [9], " "Information adaptation in urban design [10]," "Information and self-organization [11]," "Information and self-organization: a unifying approach and applications [12], " and in these articles, he not only makes a case study of the relationship between specific self-organizing systems such as biological systems, brain dynamic systems, urban design systems and information but also conducted an in-depth discussion on the relationship between information and selforganization. However, he explained the self-organization process mainly based on the level of information science, such as Shannon's grammatical information theory and other scholars' relevant semantic information and information science of pragmatic information.…”