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  1. Olle Blomberg (2011). Conceptions of Cognition for Cognitive Engineering. International Journal of Aviation Psychology 21 (1):85-104.
    Cognitive processes, cognitive psychology tells us, unfold in our heads. In contrast, several approaches in cognitive engineering argue for a shift of unit of analysis from what is going on in the heads of operators to the workings of whole socio-technical systems. This shift is sometimes presented as part of the development of a new understanding of what cognition is and where the boundaries of cognitive systems are. Cognition, it is claimed, is not just situated or embedded, but extended and (...)
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  2. Salvo D.’Agostino (2012). Newton, Ampère, Maxwell, Einstein: sulla deduzione dei fenomeni. In Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (eds.), Complessità e Riduzionismo. © ISONOMIA – Epistemologica, University of Urbino 54-64.
    Il tema della complessità della scienza è stato da qualche decennio oggetto di una vasta letteratura sia sul versante più strettamente scientifico, sia sul piano filosofico. Un argomento emerso con notevole interesse ha riguardato un aspetto della complessità inteso come rinuncia a una generalizzazione dei procedimenti assiomatico-deduttivi come metodo generale della ricerca scientifica. È stata espressa la convinzione che la fisica pre-relativistica sia stata fondata prevalentemente sul trionfo di questo metodo, sulla scia, fra l’altro, della gloriosa tradizione dei Principia newtoniani. (...)
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  3. Daniel Estrada & Jon Lawhead (2013). Gaming the Attention Economy. In Pietro Michelucci (ed.), The Handbook of Human Computation. Springer 961-978.
    The future of human computation benefits from examining tasks that agents already perform and designing environments to give those tasks computational significance. We call this natural human computation. We consider the possible future of NHC through the lens of Swarm!, an application under development for Google Glass. Swarm! motivates users to compute the solutions to a class of economic optimization problems by engaging the attention dynamics of crowds. We argue that anticipating and managing economies of attention provides one of the (...)
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  4. Luis H. Favela (2015). Understanding Cognition Via Complexity Science. Dissertation, University of Cincinnati
    Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As such it is (...)
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  5. Aldo Filomeno (2014). On the Possibility of Stable Regularities Without Fundamental Laws. Dissertation, Autonomous University of Barcelona
    This doctoral dissertation investigates the notion of physical necessity. Specifically, it studies whether it is possible to account for non-accidental regularities without the standard assumption of a pre-existent set of governing laws. Thus, it takes side with the so called deflationist accounts of laws of nature, like the humean or the antirealist. The specific aim is to complement such accounts by providing a missing explanation of the appearance of physical necessity. In order to provide an explanation, I recur to fields (...)
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  6. Aldo Filomeno (2014). Recensione di Michael Strevens' "Bigger than chaos. Understanding complexity through probability". [REVIEW] Aphex 10.
  7. 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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  8. 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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  9. James Franklin (1999). Structure and Domain-Independence in the Formal Sciences. Studies in History and Philosophy of Science 30:721-723.
    Replies to Kevin de Laplante’s ‘Certainty and Domain-Independence in the Sciences of Complexity’ (de Laplante, 1999), defending the thesis of J. Franklin, ‘The formal sciences discover the philosophers’ stone’, Studies in History and Philosophy of Science, 25 (1994), 513-33, that the sciences of complexity can combine certain knowledge with direct applicability to reality.
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  10. Ulrich J. Frey & Hannes Rusch (2014). Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets. World Development 59:93-103.
    The influence of many factors on ecological success in common pool resource management is still unclear. This may be due to methodological issues. These include causal complexity, a lack of large-N-studies and nonlinear relationships between factors. We address all three issues with a new methodological approach, artificial neural networks, which is discussed in detail. It allows us to develop a model with comparably high predictive power. In addition, two success factors are analyzed: legal security and institutional fairness. Both factors show (...)
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  11. Alexandre Guay (2009). Symétries, brisures de symétries et complexité en mathématiques, physique et biologie Luciano Boi, dir. Bern, Peter Lang , 2006, 297 p. [REVIEW] Dialogue 48 (4):900-902.
    Compte rendu de L. Boi, Symétries, brisures de symétries et complexité en mathématiques, physique et biologie, Peter Lang.
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  12. Cliff Hooker (ed.) (2011). Philosophy of Complex Systems (Handbook of the Philosophy of Science, Vol. 10). North Holland.
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  13. 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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  14. 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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  15. Jon Lawhead (2012). Getting Fundamental About Doing Physics in The Big Bang. In Dean Kowalski (ed.), The Big Bang Theory and Philosophy. Blackwell 99-111.
  16. Conor Mayo-Wilson (2015). Structural Chaos. Philosophy of Science 82 (5):1236-1247.
    A dynamical system is called chaotic if small changes to its initial conditions can create large changes in its behavior. By analogy, we call a dynamical system structurally chaotic if small changes to the equations describing the evolution of the system produce large changes in its behavior. Although there are many definitions of “chaos,” there are few mathematically precise candidate definitions of “structural chaos.” I propose a definition, and I explain two new theorems that show that a set of models (...)
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  17. Michel Rosenfeld (1991). Antopoiesis and Justice a Critique of Luhmann's Conception of Law. Faculty of Law, University of Toronto.
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  18. Arcangelo Rossi (2012). Dai modelli riduzionistici della realtà fisica nella scienza classica alla complessità nella scienza contemporanea. In Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (eds.), Complessità e Riduzionismo. © ISONOMIA – Epistemologica, University of Urbino 82-98.
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  19. Yaroslav Sergeyev (2011). Using Blinking Fractals for Mathematical Modelling of Processes of Growth in Biological Systems. Informatica 22 (4):559–576.
    Many biological processes and objects can be described by fractals. The paper uses a new type of objects – blinking fractals – that are not covered by traditional theories considering dynamics of self-similarity processes. It is shown that both traditional and blinking fractals can be successfully studied by a recent approach allowing one to work numerically with infinite and infinitesimal numbers. It is shown that blinking fractals can be applied for modeling complex processes of growth of biological systems including their (...)
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  20. Yaroslav Sergeyev, Dmitri Iudin & Masaschi Hayakawa (2012). Interpretation of Percolation in Terms of Infinity Computations. Applied Mathematics and Computation 218 (16):8099-8111.
    In this paper, a number of traditional models related to the percolation theory has been considered by means of new computational methodology that does not use Cantor’s ideas and describes infinite and infinitesimal numbers in accordance with the principle ‘The part is less than the whole’. It gives a possibility to work with finite, infinite, and infinitesimal quantities numerically by using a new kind of a compute - the Infinity Computer – introduced recently in [18]. The new approach does not (...)
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  21. Roberto Serra (2012). Complex Systems Biology. In Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (eds.), Complessità e Riduzionismo. 100-107.
    The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, which (...)
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  22. S. J. Stoeger (2007). Evolution and Emergence: Systems, Organisms, Persons. OUP Oxford.
    A collection of essays by experts in the field, exploring how nature works to produce systems of increasing complexity from simple components, and how our understanding of this phenomenon of emergence can lead us to a deeper appreciation of both our humanity and our relationship with God.
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  23. Héctor J. Sussmann & Raphael S. Zahler (1978). Catastrophe Theory as Applied to the Social and Biological Sciences: A Critique. Synthese 37 (2):117 - 216.
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  24. Georg Theiner (2011). Review of John Bolender (2010). The Self-Organizing Social Mind. [REVIEW] Notre Dame Philosophical Reviews.
  25. Giorgio Turchetti (2012). Dai modelli fisici ai sistemi complessi. In Vincenzo Fano, Enrico Giannetto, Giulia Giannini & Pierluigi Graziani (eds.), Complessità e Riduzionismo. © ISONOMIA – Epistemologica, University of Urbino 108-125.
    L’osservazione della natura con l’intento di capire l’origine della varietà di forme e fenomeni in cui si manifesta ha origini remote. All’inizio il rapporto con i fenomeni naturali era dominato da sentimenti quali paura e stupore che conducevano a supporre l’esistenza di entità sfuggenti alla percezione diretta che permeavano gli elementi animandoli. Ecco dunque che la magia rappresenta l’elemento dominante della filosofia naturale primitiva caratterizzata da una unicità degli eventi e dalla impossibilità di capirli e dominarli in quanto frutto della (...)
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  26. P. Ylikoski (2009). Book Review: Sawyer, R. Keith. (2005). Social Emergence: Societies as Complex Systems. Cambridge, UK: Cambridge University Press. [REVIEW] Philosophy of the Social Sciences 39 (3):527-530.
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