Foundations and formalizations of self-organization

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    In view of the various streams and directions of the field of self-organization, it is beyond the present introductory chapter to review all the currents of research in the field. Rather, the aim of the present section is to address some of the points judged as most relevant and to provide a discussion of suitable candidate formalisms for the treatment of self-organization. In the author’s opinion, discussing formalisms is not just a vain exercise, but allows one to isolate the essence of the notion one wishes to develop. Thus even if one disagrees with the path taken (as is common in the case of not yet universally agreed upon formal notions), starting from operational formalisms helps to serve as a compass guiding one towards notions suitable for one’s purposes. This is the philosophy of the present chapter. The chapter is structured as follows: in Sect. 2.2, we will present several central conceptual issues relevant in the context of self-organization. Some historical remarks about related relevant work are then done in Sect. 2.3. To illustrate the setting, a brief overview over some classical examples for self-organizing processes is given in Sect. 2.4. In Sects. 2.5 and 2.6, introduces the two main information-theoretic concepts of self-organization that the present chapter aims to discuss. One concept, based on the ϵ-machine formalism by Crutchfield and Shalizi, introduces self-organization as an increase of (statistical) complexity with time. The other concept will suggest measuring self-organization as an increase of mutual correlations (measured by multiinformation) between different components of a system. In Sect. 2.7, finally, important properties of these two measures as well as their distinctive characteristics (namely their power to identify temporal versus compositional self-organization) will be discussed, before Sect. 2.8 gives some conclusive remarks.
    Original languageEnglish
    Title of host publicationAdvances in Applied Self-Organizing Systems
    PublisherSpringer Nature
    Number of pages20
    ISBN (Print)9781447151128
    Publication statusPublished - 1 Jan 2013

    Publication series

    NameAdvanced Information and Knowledge Processing
    ISSN (Print)1610-3947
    ISSN (Electronic)2197-8441


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