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The study of complexity has emerged out of a number of broadly holistic trends in the physical sciences in the last century, principally in the fields of computing, cybernetics, dynamical system theory (a branch of classical mechanics which studies the properties and interactions of many-bodied systems), and thermodynamics. Contemporary complexity science can be seen as the heir to a number of earlier approaches to the problems associated with articulating a scientific approach to the study of these kinds of phenomena. Philosophical problems associated with complexity include clarifying the meanings of various concepts associated with complexity, such as emergence, non-linearity, feedback, adaptation, and self-organization, and the extent to which these terms can be given scientific meaning, that is, the extent to which these terms can be meaningfully used in the physical sciences themselves. The study of complexity also naturally intersects with more traditional problem areas in the philosophy of the sciences, such as the study of reductionism, modelling, supervenience, functionalism, and causality; however the focus of contemporary philosophy of complexity has largely tended towards the examination of (or in many cases, an attempt at the legitimation of) a scientific grounding of a particular set of approaches to these problem areas. Much of this focus is surely due to the fact that the study of complexity in the twentieth century has largely been driven by scientific practitioners themselves, and not by philosophers or philosophers of science. As such, contemporary complexity theory also makes assumptions about the relationship between scientific and philosophical theories, leading to one of its central problems: its essential ambiguity. Is complexity science a specific branch of science (for example, the study of 'complex adaptive systems'); a study of a widespread trans-disciplinary scientific phenomenon (leading to the study of, for example, various broad 'measures of complexity'); or even a general (and allegedly paradigmatic) approach to science itself (the source of many popularizations, and in some cases works bordering on pseudo-science)? This ambiguity (which is reflected in the bibliography) opens up further avenues for exploration, and has implications for the manner in which philosophers should attempt to approach the subject.

Key works Weaver 1948, Simon 1962, and Ashby 1962 are classic early works, generalizing concepts from cybernetics. Buckley 1968 is an early application to sociology and is likely the origin of the concept of a 'Complex Adaptive System', later explored in Holland 1992. Prigogine 1984 explores a model of complexity based on ideas from thermodynamics; Various proposed measures of complexity are explored in Bennett 1988, Lloyd & Pagels 1988 and Gell-Mann 1995. Kauffman 1969 and Bak 1996 are the origins of the influential models of Random Boolean Networks and Self-Organized Criticality, respectively.
Introductions A comprehensive introduction to many of the technical and philosophical issues of complexity can be found in Ladyman et al 2013. A book-length popular overview of the diverse areas of research in complexity is Mitchell 2009. Historical context is provided in Abraham 2011 and Francois 1999. There is a paucity of discussion of the subject in a manner that would be familiar to academic philosophers; in addition to Ladyman et al 2013, readers can consult Poser 2007Phelan 2001, and, on a more skeptical note, Taborsky 2014
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  1. Ralph H. Abraham (2011). The Genesis of Complexity. World Futures 67 (4-5):380 - 394.
    The theories of complexity comprise a system of great breadth. But what is included under this umbrella? Here we attempt a portrait of complexity theory, seen through the lens of complexity theory itself. That is, we portray the subject as an evolving complex dynamical system, or social network, with bifurcations, emergent properties, and so on. This is a capsule history covering the twentieth century. Extensive background data may be seen at www.visual-chaos.org/complexity.
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  2. Michel Alhadeff-Jones (2008). Three Generations of Complexity Theories: Nuances and Ambiguities. Educational Philosophy and Theory 40 (1):66–82.
    The contemporary use of the term ‘complexity’ frequently indicates that it is considered a unified concept. This may lead to a neglect of the range of different theories that deal with the implications related to the notion of complexity. This paper, integrating both the English and the Latin traditions of research associated with this notion, suggests a more nuanced use of the term, thereby avoiding simplification of the concept to some of its dominant expressions only. The paper further explores the (...)
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  3. Philip Anderson & Jack Cohen (1999). Reviews: Coping with Uncertainty, Insights From the New Sciences of Chaos, Self-Organization, and Complexity, Uri Merry. [REVIEW] Emergence: Complexity and Organization 1 (2):106-108.
    (1999). Reviews: Coping with Uncertainty, Insights from the New Sciences of Chaos, Self-Organization, and Complexity, Uri Merry. Emergence: Vol. 1, No. 2, pp. 106-108.
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  4. W. Ross Ashby (1962). Principles of the Self-Organizing System. In H. Von Foerster & Zopf Jr (eds.), Principles of Self-Organization: Transactions of the University of Illinois Symposium. Pergamon 255–278.
  5. David Aubin (2008). 'The Memory of Life Itself': Bénard's Cells and the Cinematography of Self-Organization. Studies in History and Philosophy of Science Part A 39 (3):359-369.
    In 1900, the physicist Henri Bénard exhibited the spontaneous formation of cells in a layer of liquid heated from below. Six or seven decades later, drastic reinterpretations of this experiment formed an important component of ‘chaos theory’. This paper therefore is an attempt at writing the history of this experiment, its long neglect and its rediscovery. It examines Bénard’s experiments from three different perspectives. First, his results are viewed in the light of the relation between experimental and mathematical approaches in (...)
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  6. David Aubin (1998). A Cultural History of Catastrophes and Chaos: Around the Institut des Hautes Études Scientifiques. Princeton.
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  7. David Aubin & Amy Dalmedico (2002). Writing the History of Dynamics Systems and Chaos: Longue Durée and Revolution, Disciplines and Cultures. Historia Mathematica 29:1–67.
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  8. R. Badii (1997). Complexity: Hierarchical Structures and Scaling in Physics. Cambridge University Press.
    This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety of (...)
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  9. Ion C. Baianu (2007). Categorical Ontology of Levels and Emergent Complexity: An Introduction. [REVIEW] Axiomathes 17 (3-4):209-222.
    An overview of the following three related papers in this issue presents the Emergence of Highly Complex Systems such as living organisms, man, society and the human mind from the viewpoint of the current Ontological Theory of Levels. The ontology of spacetime structures in the Universe is discussed beginning with the quantum level; then, the striking emergence of the higher levels of reality is examined from a categorical—relational and logical viewpoint. The ontological problems and methodology aspects discussed in the first (...)
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  10. Per Bak (1996). How Nature Works: The Science of Self-Organized Criticality. Copernicus.
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  11. Robert W. Batterman (1991). Randomness and Probability in Dynamical Theories: On the Proposals of the Prigogine School. Philosophy of Science 58 (2):241-263.
    I discuss recent work in ergodic theory and statistical mechanics, regarding the compatibility and origin of random and chaotic behavior in deterministic dynamical systems. A detailed critique of some quite radical proposals of the Prigogine school is given. I argue that their conclusion regarding the conceptual bankruptcy of the classical conceptions of an exact microstate and unique phase space trajectory is not completely justified. The analogy they want to draw with quantum mechanics is not sufficiently close to support their most (...)
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  12. Robert W. Batterman & Homer White (1996). Chaos and Algorithmic Complexity. Foundations of Physics 26 (3):307-336.
    Our aim is to discover whether the notion of algorithmic orbit-complexity can serve to define “chaos” in a dynamical system. We begin with a mostly expository discussion of algorithmic complexity and certain results of Brudno, Pesin, and Ruelle (BRP theorems) which relate the degree of exponential instability of a dynamical system to the average algorithmic complexity of its orbits. When one speaks of predicting the behavior of a dynamical system, one usually has in mind one or more (...)
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  13. C. H. Bennett (1988). Logical Depth and Physical Complexity. In R. Herken (ed.), The universal Turing machine, a half century survey. Oxford U.P. 227-257.
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  14. Charles H. Bennett (1986). On the Nature and Origin of Complexity in Discrete, Homogeneous, Locally-Interacting Systems. Foundations of Physics 16 (6):585-592.
    The observed complexity of nature is often attributed to an intrinsic propensity of matter to self-organize under certain (e.g., dissipative) conditions. In order better to understand and test this vague thesis, we define complexity as “logical depth,” a notion based on algorithmic information and computational time complexity. Informally, logical depth is the number of steps in the deductive or causal path connecting a thing with its plausible origin. We then assess the effects of dissipation, noise, and spatial and other symmetries (...)
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  15. Walter Buckley (1968). Society as a Complex Adaptive System. In Modern Systems Research for the Behavioral Scientist. Aldine
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  16. Brian Castellani & Frederick William Hafferty (eds.) (2009). Sociology and Complexity Science. Springer.
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  17. Geoffrey K. Chambers (2015). Understanding Complexity: Are We Making Progress? Biology and Philosophy 30 (5):747-756.
    In recent years a new conceptual tool called Complexity Theory has come to the attention of scientists and philosophers. This approach is concerned with the emergent properties of interacting systems. It has found wide applicability from cosmology to Social Structure Analysis. However, practitioners are still struggling to find the best way to define complexity and then to measure it. A new book Complexity and the arrow of time by Lineweaver et al. contains contributions from scholars who provide critical reviews of (...)
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  18. Paul Cilliers (1998). Complexity and Postmodernism: Understanding Complex Systems. Routledge.
    Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.
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  19. Tim Crowther, On Describing the Total Universe as the Non-Self-Similar Fractal (NSSF) Set.
    One conceptual question has been puzzling people for a long time: As the observable universe has been expanding, what has it been expanding into and where did it come from? In this essay I will combine the two questions above to one: What is the Total Universe? I will begin attempt to develop such a description by examining the linguistic human limitations because I believe that this language barrier between our evolved language and a description of the total universe can (...)
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  20. Tanya De Villiers (2002). Complexity and the Self. Dissertation, University of Stellenbosch
    In this thesis it is argued that the age-old philosophical "Problem of the Self' can benefit by being approached from the perspective of a relatively recent science, namely that of Complexity Theory. With this in mind the conceptual features of this theory is highlighted and summarised. Furthermore, the argument is made that the predominantly dualistic approach to the self that is characteristic of the Western Philosophical tradition serves to hinder, rather than edify, our understanding of the phenomenon. The benefits posed (...)
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  21. Laurent Dobuzinskis (2004). Where is Morin's Road to Complexity Going? World Futures 60 (5 & 6):433 – 455.
    Edgar Morin took an early lead within the French intellectual community, but also in comparison with parallel reflections in the English-speaking world, as far as critical discussion of the epistemology of the new sciences of complexity is concerned. His "complex thought" raises many intriguing questions and offers a dazzling synthesis of a wide range of fields, from physics to biology to psychology and the social sciences. However, Morin's road to complexity bypasses some crucial issues in philosophy and political economy. Therefore, (...)
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  22. Claus Emmeche (1997). Aspects of Complexity in Life and Science. Philosophica 59.
    A short review of <span class='Hi'>complexity</span> research from the perspective of history and philosophy of biology is presented. <span class='Hi'>Complexity</span> and its emergence has scientific and metaphysical meanings. From its beginning, biology was a science of complex systems, but with the advent of electronic computing and the possibility of simulating mathematical models of complicated systems, new intuitions of <span class='Hi'>complexity</span> emerged, together with attempts to devise quantitative measures of <span class='Hi'>complexity</span>. But can we quantify the complex?
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  23. Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (2012). Complessità E Riduzionismo. ISONOMIA - Epistemologica Series Editor.
    The enormous increasing of connections between people and the noteworthy enlargement of domains and methods in sciences have augmented extraordinarily the cardinality of the set of meaningful human symbols. We know that complexity is always on the way to become complication, i.e. a non-tractable topic. For this reason scholars engage themselves more and more in attempting to tame plurality and chaos. In this book distinguished scientists, philosophers and historians of science reflect on the topic from a multidisciplinary point of view. (...)
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  24. Luis H. Favela (2014). Radical Embodied Cognitive Neuroscience: Addressing “Grand Challenges” of the Mind Sciences. Frontiers in Human Neuroscience 8:01-10.
    It is becoming ever more accepted that investigations of mind span the brain, body, and environment. To broaden the scope of what is relevant in such investigations is to increase the amount of data scientists must reckon with. Thus, a major challenge facing scientists who study the mind is how to make big data intelligible both within and between fields. One way to face this challenge is to structure the data within a framework and to make it intelligible by means (...)
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  25. Andrew A. Fingelkurts & Alexander A. Fingelkurts (2013). Dissipative Many-Body Model and a Nested Operational Architectonics of the Brain. Physics of Life Reviews 10:103-105.
    This paper briefly review a current trend in neuroscience aiming to combine neurophysiological and physical concepts in order to understand the emergence of spatio-temporal patterns within brain activity by which brain constructs knowledge from multiple streams of information. The authors further suggest that the meanings, which subjectively are experienced as thoughts or perceptions can best be described objectively as created and carried by large fields of neural activity within the operational architectonics of brain functioning.
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  26. Andrew A. Fingelkurts, Alexander A. Fingelkurts & Carlos F. H. Neves (2013). Consciousness as a Phenomenon in the Operational Architectonics of Brain Organization: Criticality and Self-Organization Considerations. Chaos, Solitons and Fractals 55:13-31.
    In this paper we aim to show that phenomenal consciousness is realized by a particular level of brain operational organization and that understanding human consciousness requires a description of the laws of the immediately underlying neural collective phenomena, the nested hierarchy of electromagnetic fields of brain activity – operational architectonics. We argue that the subjective mental reality and the objective neurobiological reality, although seemingly worlds apart, are intimately connected along a unified metastable continuum and are both guided by the universal (...)
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  27. Andy Forceno, Thermodynamics and the Evolution of Life.
    This paper explores the connection between the 2nd thermodynamics and the emergence and evolution of life on Earth. 60 years ago, Erwin Schrodinger understood that the thermodynamically-open nature of living systems exempted them from the constraints imposed by the second law, but it was not clear why such systems should exist at all. Now we’re coming to realize that, not only are open systems ubiquitous, but they are likely, and perhaps even necessary. Some open systems are characterized as dissipative, and (...)
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  28. Charles Francois (1999). Systemics and Cybernetics in a Historical Perspective. Systems Research and Behavioral Science 16 (3):203-219.
  29. Murray Gell-Mann (1995). What is Complexity?Remarks on Simplicity and Complexity by the Nobel Prize-Winning Author ofThe Quark and the Jaguar. Complexity 1 (1):16-19.
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  30. J. Guckenheimer (1978). The Catastrophe Controversy. The Mathematical Intelligencer 1.
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  31. Amit Hagar, Thou Shalt Not Commute!
    For many among the scientifically informed public, and even among physicists, Heisenberg's uncertainty principle epitomizes quantum mechanics. Nevertheless, more than 86 years after its inception, there is no consensus over the interpretation, scope, and validity of this principle. The aim of this chapter is to offer one such interpretation, the traces of which may be found already in Heisenberg's letters to Pauli from 1926, and in Dirac's anticipation of Heisenberg's uncertainty relations from 1927, that stems form the hypothesis of finite (...)
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  32. Amit Hagar (forthcoming). Review of M. Thalos' "Without Hierarchy". [REVIEW] Notre Dame Philosophical Reviews.
  33. Hermann Haken & Helena Knyazeva (2000). Synergetik: zwischen Reduktionismus und Holismus. Philosophia Naturalis 37 (1):21-44.
    Die philosophischen Folgerungen der Synergetik, einer interdisziplinären Theorie der Evolution und Selbstorganisation komplexer nichtlinearer Systeme, werden in diesem Artikel zur Diskussion gestellt. Das sind der weltanschauliche Sinn des Begriffs von der „Nichtlinearität“, die konstruktive Rolle des Chaos in der Evolution, eine neue Vorstellung von diskreten Spektren evolutionärer Wege in komplexen Systemen, die Prinzipien des Aufbaus von komplexem evolutionärem Ganzen, der Integration von komplexen Strukturen, die sich mit verschiedenen Geschwindigkeiten entwickeln, die Methoden des nichtlinearen Managements komplexer Systeme. Die Synergetik entdeckt allgemeingültige (...)
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  34. Meir Hemmo & Orly Shenker (2015). The Emergence of Macroscopic Regularity. Mind and Society 14 (2):221-244.
    Special sciences (such as biology, psychology, economics) describe various regularities holding at some high macroscopic level. One of the central questions concerning these macroscopic regularities is how they are related to the laws of physics governing the underlying microscopic physical reality. In this paper we show how a macroscopic regularity may emerge from an underlying micro- scopic structure, and how the appearance of multiple realizability of the special sciences by physics comes about in a reductionist-physicalist framework. On this basis we (...)
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  35. J. H. Holland (1992). Complex Adaptive Systems. Daedalus 121 (1):17-30.
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  36. John Horgan (1996). On Complexity and the End of Science: What's Wrong with Complexity. Complexity 2 (2):13-15.
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  37. John Horgan (1995). Trends in Complexity Studies: From Complexity to Perplexity. Scientific American 272:74–9.
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  38. Stuart Kauffman (1969). Homeostasis and Differentiation in Random Genetic Control Networks. Nature 224:177-178.
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  39. John J. Kineman (2011). Relational Science: A Synthesis. [REVIEW] Axiomathes 21 (3):393-437.
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  40. Helena Knyazeva (2009). Nonlinear Cobweb of Cognition. Foundations of Science 14 (3):167-179.
    The modern conception of enactive cognition is under discussion from the standpoint concerning the notions of nonlinear dynamics and synergetics. The contribution of Francisco Varela and his precursors is considered. It is shown that the perceptual and mental processes are bound up with the “architecture” of human body and nonlinear and circular connecting links between the subject of cognition and the world constructed by him can be metaphorically called a nonlinear cobweb of cognition. Cognition is an autopoietic activity because it (...)
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  41. Helena Knyazeva (2005). Figures of Time in Evolution of Complex Systems. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 36 (2):289 - 304.
    Owing to intensive development of the theory of self-organization of complex systems called also synergetics, profound changes in our notions of time occur. Whereas at the beginning of the 20th century, natural sciences, by picking up the general spirit of Einstein's theory of relativity, consider a geometrization as an ideal, i.e. try to represent time and force interactions through space and the changes of its properties, nowadays, at the beginning of the 21st century, time turns to be in the focus (...)
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  42. Helena Knyazeva (2004). The Complex Nonlinear Thinking: Edgar Morin's Demand of a Reform of Thinking and the Contribution of Synergetics. World Futures 60 (5 & 6):389 – 405.
    Main principles of the complex nonlinear thinking which are based on the notions of the modern theory of evolution and self-organization of complex systems called also synergetics are under discussion in this article. The principles are transdisciplinary, holistic, and oriented to a human being. The notions of system complexity, nonlinearity of evolution, creative chaos, space-time definiteness of structure-attractors of evolution, resonant influences, nonlinear and soft management are here of great importance. In this connection, a prominent contribution made to (...)
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  43. Helena Knyazeva (2003). Self-Reflective Synergetics. Systems Research and Behavioral Science 20 (1):53-64.
    An attempt to critically analyse the claims of the theory of self-organization of complex systems (synergetics) to the interdisciplinary generalizations and the universal efficacy of its models is made in the paper. The grounds for transfer of synergetic models to different disciplinary fields are under discussion. It is argued that synergetics is a mental scheme or a heuristic approach to exploring the complex behaviour of systems, rather than a universal key to solving concrete scientific problems. The prospects for development and (...)
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  44. Helena Knyazeva (1999). Synergetics and the Images of Future. Futures 31 (3):281-290.
    The hope of finding new methods of predicting the course of historical processes could be connected with the recent developments of the theory of self-organisation, also called synergetics. It provides us with knowledge of constructive principles of co-evolution of complex social systems, co-evolution of countries and geopolitical regions being at different stages of development, integration of the East and the West, the North and the South. Due to the growth of population on the Earth in blow-up regime, the general and (...)
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  45. Helena Knyazeva (1998). The Synergetic View of Human Creativity. Evolution and Cognition 4 (2):145-155.
    The heuristic value of synergetic models of evolving and self-organizing complex systems as well as their application to epistemological problems is shown in this paper. Nonlinear synergetic models turn out to be fruitful in comprehending epistemological problems such as the nature of human creativity, the functioning of human intuition and imagination, the historical development of science and culture. In the light of synergetics creative thinking can be viewed as a selforganization and self-completion of images and thoughts, filling up gaps in (...)
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  46. Harry Kunneman (forthcoming). General Complexity, Ethical Complexity and Normative Professionalization. Foundations of Science:1-5.
    This article addresses the critical comments that focus on what is perceived as lack of clarity with regard to different uses of the system concept: on the one hand, in the usual general sense, on the other, in a specific ‘Habermassian’ sense. This final reply tries to remedy this in critical discussion with Morin, arguing that Morin’s paradigm of generalized complexity addresses the question of what subjects are, but remains silent with regard to the question of who they are. Answering (...)
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  47. James Ladyman, James Lambert & Karoline Wiesner (2013). What is a Complex System? European Journal for Philosophy of Science 3 (1):33-67.
    Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with (...)
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  48. Rolf Landauer (1988). A Simple Measure of Complexity. Nature 336.
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  49. Jon Lawhead (forthcoming). Structural Modeling Error and the System Individuation Problem. British Journal for the Philosophy of Science.
    Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, and the (...)
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  50. Charles H. Lineweaver, Paul C. W. Davies & Michael Ruse (eds.) (2013). Complexity and the Arrow of Time. Cambridge U.P..
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