Search results for 'Complexity' (try it on Scholar)

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  1. Franck Varenne (2009). Models and Simulations in the Historical Emergence of the Science of Complexity. In Ma Aziz-Alaoui & C. Bertelle (eds.), From System Complexity to Emergent Properties. Springer. 3--21.score: 21.0
    As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation (...)
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  2. R. Brown, J. F. Glazebrook & I. C. Baianu (2007). A Conceptual Construction of Complexity Levels Theory in Spacetime Categorical Ontology: Non-Abelian Algebraic Topology, Many-Valued Logics and Dynamic Systems. [REVIEW] Axiomathes 17 (3-4):409-493.score: 18.0
    A novel conceptual framework is introduced for the Complexity Levels Theory in a Categorical Ontology of Space and Time. This conceptual and formal construction is intended for ontological studies of Emergent Biosystems, Super-complex Dynamics, Evolution and Human Consciousness. A claim is defended concerning the universal representation of an item’s essence in categorical terms. As an essential example, relational structures of living organisms are well represented by applying the important categorical concept of natural transformations to biomolecular reactions and relational structures (...)
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  3. Deborah Osberg, Gert Biesta & Paul Cilliers (2008). From Representation to Emergence: Complexity's Challenge to the Epistemology of Schooling. Educational Philosophy and Theory 40 (1):213–227.score: 18.0
    In modern, Western societies the purpose of schooling is to ensure that school-goers acquire knowledge of pre-existing practices, events, entities and so on. The knowledge that is learned is then tested to see if the learner has acquired a correct or adequate understanding of it. For this reason, it can be argued that schooling is organised around a representational epistemology: one which holds that knowledge is an accurate representation of something that is separate from knowledge itself. Since the object of (...)
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  4. Paul Cilliers (1998). Complexity and Postmodernism: Understanding Complex Systems. Routledge.score: 18.0
    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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  5. Robert B. Northrop (2010). Introduction to Complexity and Complex Systems. Taylor & Francis.score: 18.0
    Introduction to complexity and complex systems -- Introduction to large linear systems -- Introduction to biochemical oscillators and nonlinear biochemical systems -- Modularity, redundancy, degeneracy, pleiotropy and robustness in complex biological systems -- The evolution of biological complexity; invertebrate immune systems -- Irreducible and specified complexity in living systems -- The complex adaptive and innate human immune systems -- Complexity in quasispecies : microRNAs -- Introduction to complexity in economic systems -- Complexity in quasispecies (...)
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  6. Peter Godfrey-Smith (1996). Complexity and the Function of Mind in Nature. Cambridge University Press.score: 18.0
    This book explains the relationship between intelligence and environmental complexity, and in so doing links philosophy of mind to more general issues about the relations between organisms and environments, and to the general pattern of 'externalist' explanations. The author provides a biological approach to the investigation of mind and cognition in nature. In particular he explores the idea that the function of cognition is to enable agents to deal with environmental complexity. The history of the idea in the (...)
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  7. Shaun Nichols & Todd A. Grantham (2000). Adaptive Complexity and Phenomenal Consciousness. Philosophy Of Science 67 (4):648-670.score: 18.0
    Arguments about the evolutionary function of phenomenal consciousness are beset by the problem of epiphenomenalism. For if it is not clear whether phenomenal consciousness has a causal role, then it is difficult to begin an argument for the evolutionary role of phenomenal consciousness. We argue that complexity arguments offer a way around this problem. According to evolutionary biology, the structural complexity of a given organ can provide evidence that the organ is an adaptation, even if nothing is known (...)
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  8. Jaime Nubiola (2001). Peirce on Complexity. In Schmitz Walter (ed.), Proceedings of the 7th International Congress of the IASS-AIS.score: 18.0
    In a world of ever growing specialization, the issue of complexity attracts a good amount of attention from cross-disciplinary points of view as this Congress provides evidence. Charles S. Peirce's thought may help us not only to shoulder once again philosophical responsibility which has been largely abdicated by much of 20th century philosophy, but also to tackle some of the most stubborn contemporary problems. The founder of pragmatism identified one century ago most of these problems, and he also mapped (...)
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  9. Carlo Cellucci (1985). Proof Theory and Complexity. Synthese 62 (2):173 - 189.score: 18.0
    Different proofs may be distinguished in terms of complexity. This paper reviews the inefficiency of current logical systems.
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  10. Jakub Szymanik (2009). Quantifiers in TIME and SPACE. Computational Complexity of Generalized Quantifiers in Natural Language. Dissertation, University of Amsterdamscore: 18.0
    In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in (...)
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  11. Mark Mason (2008). Complexity Theory and the Philosophy of Education. Educational Philosophy and Theory 40 (1):4–18.score: 18.0
    This volume provides an accessible theoretical introduction to the topic of complexity theory while considering its broader implications for educational change.
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  12. Matthias Scheutz (2001). Computational Vs. Causal Complexity. Minds And Machines 11 (4):543-566.score: 18.0
    The main claim of this paper is that notions of implementation based on an isomorphic correspondence between physical and computational states are not tenable. Rather, ``implementation'' has to be based on the notion of ``bisimulation'' in order to be able to block unwanted implementation results and incorporate intuitions from computational practice. A formal definition of implementation is suggested, which satisfies theoretical and practical requirements and may also be used to make the functionalist notion of ``physical realization'' precise. The upshot of (...)
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  13. Graeme S. Halford, William H. Wilson & Steven Phillips (1998). Processing Capacity Defined by Relational Complexity: Implications for Comparative, Developmental, and Cognitive Psychology. Behavioral and Brain Sciences 21 (6):803-831.score: 18.0
    Working memory limits are best defined in terms of the complexity of the relations that can be processed in parallel. Complexity is defined as the number of related dimensions or sources of variation. A unary relation has one argument and one source of variation; its argument can be instantiated in only one way at a time. A binary relation has two arguments, two sources of variation, and two instantiations, and so on. Dimensionality is related to the number of (...)
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  14. Jakub Szymanik (2010). Computational Complexity of Polyadic Lifts of Generalized Quantifiers in Natural Language. Linguistics and Philosophy 33 (3):215-250.score: 18.0
    We study the computational complexity of polyadic quantifiers in natural language. This type of quantification is widely used in formal semantics to model the meaning of multi-quantifier sentences. First, we show that the standard constructions that turn simple determiners into complex quantifiers, namely Boolean operations, iteration, cumulation, and resumption, are tractable. Then, we provide an insight into branching operation yielding intractable natural language multi-quantifier expressions. Next, we focus on a linguistic case study. We use computational complexity results to (...)
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  15. Hans Poser (2007). Theories of Complexity and Their Problems. Frontiers of Philosophy in China 2 (3):423-436.score: 18.0
    Complexity theories are on the way to establish a new worldview—processes instead of objects, history and uniqueness of everything instead of repetition and lawlikeness are the elements. These theories from deterministic chaos via the dissipative structures, the theory of catastrophes, self organization and synergetics are mathematical models, connected with a new understanding of science. They are characterized by new fundamental commitments of sciences. But at the same time, they are characterized by epistemic boundaries.
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  16. Daniel W. McShea (1991). Complexity and Evolution: What Everybody Knows. [REVIEW] Biology and Philosophy 6 (3):303-324.score: 18.0
    The consensus among evolutionists seems to be (and has been for at least a century) that the morphological complexity of organisms increases in evolution, although almost no empirical evidence for such a trend exists. Most studies of complexity have been theoretical, and the few empirical studies have not, with the exception of certain recent ones, been especially rigorous; reviews are presented of both the theoretical and empirical literature. The paucity of evidence raises the question of what sustains the (...)
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  17. Börje Ekstig (2010). Complexity and Evolution: A Study of the Growth of Complexity in Organic and Cultural Evolution. [REVIEW] Foundations of Science 15 (3):263-278.score: 18.0
    In the present paper I develop a model of the evolutionary process associated to the widespread although controversial notion of a prevailing trend of increasing complexity over time. The model builds on a coupling of evolution to individual developmental programs and introduces an integrated view of evolution implying that human culture and science form a continuous extension of organic evolution. It is formed as a mathematical model that has made possible a quantitative estimation in relative terms of the growth (...)
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  18. Marcin Mostowski & Jakub Szymanik (2007). Computational Complexity of Some Ramsey Quantifiers in Finite Models. Bulletin of Symbolic Logic 13:281--282.score: 18.0
    The problem of computational complexity of semantics for some natural language constructions – considered in [M. Mostowski, D. Wojtyniak 2004] – motivates an interest in complexity of Ramsey quantifiers in finite models. In general a sentence with a Ramsey quantifier R of the following form Rx, yH(x, y) is interpreted as ∃A(A is big relatively to the universe ∧A2 ⊆ H). In the paper cited the problem of the complexity of the Hintikka sentence is reduced to the (...)
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  19. Melanie Mitchell (2009). Complexity: A Guided Tour. Oxford University Press.score: 18.0
    What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex (...)
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  20. Jakub Szymanik (2009). The Computational Complexity of Quantified Reciprocals. In Peter Bosch, David Gabelaia & Jérôme Lang (eds.), Lecture Notes on Artificial Intelligence 5422, Logic, Language, and Computation 7th International Tbilisi Symposium on Logic, Language, and Computation. Springer.score: 18.0
    We study the computational complexity of reciprocal sentences with quantified antecedents. We observe a computational dichotomy between different interpretations of reciprocity, and shed some light on the status of the so-called Strong Meaning Hypothesis.
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  21. Theodor Leiber (1999). Deterministic Chaos and Computational Complexity: The Case of Methodological Complexity Reductions. [REVIEW] Journal for General Philosophy of Science 30 (1):87-101.score: 18.0
    Some problems rarely discussed in traditional philosophy of science are mentioned: The empirical sciences using mathematico-quantitative theoretical models are frequently confronted with several types of computational problems posing primarily methodological limitations on explanatory and prognostic matters. Such limitations may arise from the appearances of deterministic chaos and (too) high computational complexity in general. In many cases, however, scientists circumvent such limitations by utilizing reductional approximations or complexity reductions for intractable problem formulations, thus constructing new models which are (...)
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  22. Tamsin Haggis (2008). 'Knowledge Must Be Contextual': Some Possible Implications of Complexity and Dynamic Systems Theories for Educational Research. Educational Philosophy and Theory 40 (1):158–176.score: 18.0
    It is now widely accepted that qualitative and quantitative research traditions, rather than being seen as opposed to or in competition with each other ( Hammersley & Atkinson, 1995 ; Furlong, 2004) should be used, where appropriate, in some kind of combination (Bryman & Cramer, 1999; Moore et al., 2003). How this combining is to be understood ontologically, and therefore epistemologically, however, is not always clear. Rather than endlessly discussing the relationship between different approaches, this paper explores some of the (...)
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  23. Jacques Ricard (1999). Biological Complexity and the Dynamics of Life Processes. Elsevier.score: 18.0
    The aim of this book is to show how supramolecular complexity of cell organization can dramatically alter the functions of individual macromolecules within a cell. The emergence of new functions which appear as a consequence of supramolecular complexity, is explained in terms of physical chemistry. The book is interdisciplinary, at the border between cell biochemistry, physics and physical chemistry. This interdisciplinarity does not result in the use of physical techniques but from the use of physical concepts to study (...)
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  24. Mark C. Taylor (2001). The Moment of Complexity: Emerging Network Culture. University of Chicago Press.score: 18.0
    " The Moment of Complexity is a profoundly original work. In remarkable and insightful ways, Mark Taylor traces an entirely new way to view the evolution of our culture, detailing how information theory and the scientific concept of complexity can be used to understand recent developments in the arts and humanities. This book will ultimately be seen as a classic."-John L. Casti, Santa Fe Institute, author of Godel: A Life of Logic, the Mind, and Mathematics The science of (...)
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  25. Bruce Edmonds (2000). Complexity and Scientific Modelling. Foundations of Science 5 (3):379-390.score: 18.0
    It is argued that complexity is not attributable directly to systems or processes but rather to the descriptions of their `best' models, to reflect their difficulty. Thus it is relative to the modelling language and type of difficulty. This approach to complexity is situated in a model of modelling. Such an approach makes sense of a number of aspects of scientific modelling: complexity is not situated between order and disorder; noise can be explicated by approaches to excess (...)
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  26. Peter D. Grünwald & Paul M. B. Vitányi (2003). Kolmogorov Complexity and Information Theory. With an Interpretation in Terms of Questions and Answers. Journal of Logic, Language and Information 12 (4):497-529.score: 18.0
    We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and wherethey are fundamentally different. We discuss and relate the basicnotions of both theories: Shannon entropy, Kolmogorov complexity, Shannon mutual informationand Kolmogorov (``algorithmic'') mutual information. We explainhow universal coding may be viewed as a middle ground betweenthe two theories. We consider Shannon's rate distortion theory, whichquantifies useful (in a certain sense) information.We use the communication of information as our (...)
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  27. Philippe Gagnon (2013). An Improbable God Between Simplicity and Complexity: Thinking About Dawkins's Challenge. International Philosophical Quarterly 53 (4):409-433.score: 18.0
    Richard Dawkins has popularized an argument that he thinks sound for showing that there is almost certainly no God. It rests on the assumptions (1) that complex and statistically improbable things are more difficult to explain than those that are not and (2) that an explanatory mechanism must show how this complexity can be built up from simpler means. But what justifies claims about the designer’s own complexity? One comes to a different understanding of order and of simplicity (...)
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  28. E. Börger (1989). Computability, Complexity, Logic. New York, N.Y., U.S.A.Elsevier Science Pub. Co..score: 18.0
    The theme of this book is formed by a pair of concepts: the concept of formal language as carrier of the precise expression of meaning, facts and problems, and the concept of algorithm or calculus, i.e. a formally operating procedure for the solution of precisely described questions and problems. The book is a unified introduction to the modern theory of these concepts, to the way in which they developed first in mathematical logic and computability theory and later in automata theory, (...)
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  29. A. Abraham, M. Werning, H. Rakoczy, D. Von Cramon & R. Schubotz (2008). Minds, Persons, and Space: An fMRI Investigation Into the Relational Complexity of Higher-Order Intentionality. Consciousness and Cognition 17 (2):438-450.score: 18.0
    Mental state reasoning or theory-of-mind has been the subject of a rich body of imaging research. Although such investigations routinely tap a common set of regions, the precise function of each area remains a contentious matter. With the help of functional magnetic resonance imaging (fMRI), we sought to determine which areas are involved when processing mental state or intentional metarepresentations by focusing on the relational aspect of such representations. Using non-intentional relational representations such as spatial relations between persons and between (...)
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  30. Samuel Coskey & Roman Kossak (2010). The Complexity of Classification Problems for Models of Arithmetic. Bulletin of Symbolic Logic 16 (3):345-358.score: 18.0
    We observe that the classification problem for countable models of arithmetic is Borel complete. On the other hand, the classification problems for finitely generated models of arithmetic and for recursively saturated models of arithmetic are Borel; we investigate the precise complexity of each of these. Finally, we show that the classification problem for pairs of recursively saturated models and for automorphisms of a fixed recursively saturated model are Borel complete.
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  31. Patrick Blackburn & Edith Spaan (1993). A Modal Perspective on the Computational Complexity of Attribute Value Grammar. Journal of Logic, Language and Information 2 (2):129-169.score: 18.0
    Many of the formalisms used in Attribute Value grammar are notational variants of languages of propositional modal logic, and testing whether two Attribute Value Structures unify amounts to testing for modal satisfiability. In this paper we put this observation to work. We study the complexity of the satisfiability problem for nine modal languages which mirror different aspects of AVS description formalisms, including the ability to express re-entrancy, the ability to express generalisations, and the ability to express recursive constraints. Two (...)
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  32. Alexander Clark & Shalom Lappin (2013). Complexity in Language Acquisition. Topics in Cognitive Science 5 (1):89-110.score: 18.0
    Learning theory has frequently been applied to language acquisition, but discussion has largely focused on information theoretic problems—in particular on the absence of direct negative evidence. Such arguments typically neglect the probabilistic nature of cognition and learning in general. We argue first that these arguments, and analyses based on them, suffer from a major flaw: they systematically conflate the hypothesis class and the learnable concept class. As a result, they do not allow one to draw significant conclusions about the learner. (...)
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  33. Daniel W. McShea (2000). Functional Complexity in Organisms: Parts as Proxies. [REVIEW] Biology and Philosophy 15 (5):641-668.score: 18.0
    The functional complexity, or the number of functions, of organisms hasfigured prominently in certain theoretical and empirical work inevolutionary biology. Large-scale trends in functional complexity andcorrelations between functional complexity and other variables, such assize, have been proposed. However, the notion of number of functions hasalso been operationally intractable, in that no method has been developedfor counting functions in an organism in a systematic and reliable way.Thus, studies have had to rely on the largely unsupported assumption thatnumber of (...)
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  34. Anthony Dardis (1995). Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research. Metaphilosophy 26 (4):435-440.score: 18.0
    Book review of Bechtel and Richardson, Discovering Complexity (1993). Review suggests that one theme of the book -- that scientific reason is "constituted" in part by a cognitive strategy of finding complexity -- is not fully supported.
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  35. Verónica Becher & Santiago Figueira (2005). Kolmogorov Complexity for Possibly Infinite Computations. Journal of Logic, Language and Information 14 (2):133-148.score: 18.0
    In this paper we study the Kolmogorov complexity for non-effective computations, that is, either halting or non-halting computations on Turing machines. This complexity function is defined as the length of the shortest input that produce a desired output via a possibly non-halting computation. Clearly this function gives a lower bound of the classical Kolmogorov complexity. In particular, if the machine is allowed to overwrite its output, this complexity coincides with the classical Kolmogorov complexity for halting (...)
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  36. Jennifer Wells (2012). Complexity and Sustainability. Routledge.score: 18.0
    Introduction -- Elucidating complexity theories -- Complexity in the natural sciences -- Complexity in social theory -- Towards transdisciplinarity -- Complexity in philosophy: complexification and the limits to knowledge -- Complexity in ethics -- Earth in the anthropocene -- Complexity and climate change -- American dreams, ecological nightmares and new visions -- Complexity and sustainability: wicked problems, gordian knots and synergistic solutions -- Conclusion.
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  37. Peter Allen, Steve Maguire & Bill McKelvey (eds.) (2011). The Sage Handbook of Complexity and Management. Sage.score: 18.0
    The SAGE Handbook of Complexity and Management will be the first substantive scholarly work to provide a map of the state of art research in the growing field ...
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  38. Adán Cabello (2006). Communication Complexity as a Principle of Quantum Mechanics. Foundations of Physics 36 (4):512-525.score: 18.0
    We introduce a two-party communication complexity problem in which the probability of success by using a particular strategy allows the parties to detect with certainty whether or not some forbidden communication has taken place. We show that theprobability of success is bounded by nature; any conceivable method which gives a probability of success outside these bounds is impossible. Moreover, any conceivable method to solve the problem which gives a probability success within these bounds is possible in nature. This example (...)
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  39. Donald Lawson Turcotte, John Rundle & Hans Frauenfelder (eds.) (2002). Self-Organized Complexity in the Physical, Biological, and Social Sciences. National Academy of Sciences.score: 18.0
    Self-organized complexity in the physical, biological, and social sciences Donald L Turcotte*f and John B. Rundle* *Department of Earth and Atmospheric ...
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  40. Guy van Orden & Damian G. Stephen (2012). Is Cognitive Science Usefully Cast as Complexity Science? Topics in Cognitive Science 4 (1):3-6.score: 18.0
    Readers of TopiCS are invited to join a debate about the utility of ideas and methods of complexity science. The topics of debate include empirical instances of qualitative change in cognitive activity and whether this empirical work demonstrates sufficiently the empirical flags of complexity. In addition, new phenomena discovered by complexity scientists, and motivated by complexity theory, call into question some basic assumptions of conventional cognitive science such as stable equilibria and homogeneous variance. The articles and (...)
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  41. Jan Krajíček (1995). Bounded Arithmetic, Propositional Logic, and Complexity Theory. Cambridge University Press.score: 18.0
    This book presents an up-to-date, unified treatment of research in bounded arithmetic and complexity of propositional logic, with emphasis on independence proofs and lower bound proofs. The author discusses the deep connections between logic and complexity theory and lists a number of intriguing open problems. An introduction to the basics of logic and complexity theory is followed by discussion of important results in propositional proof systems and systems of bounded arithmetic. More advanced topics are then treated, including (...)
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  42. Toshio Suzuki (2001). Forcing Complexity: Minimum Sizes of Forcing Conditions. Notre Dame Journal of Formal Logic 42 (2):117-120.score: 18.0
    This note is a continuation of our former paper ''Complexity of the r-query tautologies in the presence of a generic oracle.'' We give a very short direct proof of the nonexistence of t-generic oracles, a result obtained first by Dowd. We also reconstitute a proof of Dowd's result that the class of all r-generic oracles in his sense has Lebesgue measure one.
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  43. Yì N. Wáng & Thomas Ågotnes (2013). Public Announcement Logic with Distributed Knowledge: Expressivity, Completeness and Complexity. Synthese (S1):1-28.score: 18.0
    While dynamic epistemic logics with common knowledge have been extensively studied, dynamic epistemic logics with distributed knowledge have so far received far less attention. In this paper we study extensions of public announcement logic ( $\mathcal{PAL }$ ) with distributed knowledge, in particular their expressivity, axiomatisations and complexity. $\mathcal{PAL }$ extended only with distributed knowledge is not more expressive than standard epistemic logic with distributed knowledge. Our focus is therefore on $\mathcal{PACD }$ , the result of adding both common (...)
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  44. Luca Anderlini & Leonardo Felli (1999). Incomplete Contracts and Complexity Costs. Theory and Decision 46 (1):23-50.score: 18.0
    This paper investigates, in a simple risk-sharing framework, the extent to which the incompleteness of contracts could be attributed to the complexity costs associated with the writing and the implementation of contracts. We show that, given any measure of complexity in a very general class, it is possible to find simple contracting problems such that, when complexity costs are explicitly taken into account, the contracting parties optimally choose an incomplete contract which coincides with the ‘default’ division of (...)
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  45. Jarmo Kontinen (2013). Coherence and Computational Complexity of Quantifier-Free Dependence Logic Formulas. Studia Logica 101 (2):267-291.score: 18.0
    We study the computational complexity of the model checking problem for quantifier-free dependence logic ${(\mathcal{D})}$ formulas. We characterize three thresholds in the complexity: logarithmic space (LOGSPACE), non-deterministic logarithmic space (NL) and non-deterministic polynomial time (NP).
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  46. Felipe Cucker & Klaus Meer (1999). Logics Which Capture Complexity Classes Over the Reals. Journal of Symbolic Logic 64 (1):363-390.score: 18.0
    In this paper we deal with the logical description of complexity classes arising in the real number model of computation introduced by Blum, Shub, and Smale [4]. We adapt the approach of descriptive complexity theory for this model developped in [14] and extend it to capture some further complexity classes over the reals by logical means. Among the latter we find NC R , PAR R , EXP R and some others more.
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  47. Marc Goergen (ed.) (2010). Corporate Governance and Complexity Theory. Edward Elgar.score: 18.0
    Introduction -- The legal aspects -- Corporate governance and corporate performance -- Complexity and corporate governance -- Conclusion.
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  48. Michael H. G. Hoffmann (forthcoming). Changing Philosophy Through Technology: Complexity and Computer-Supported Collaborative Argument Mapping. Philosophy and Technology:1-22.score: 18.0
    Technology is not only an object of philosophical reflection but also something that can change this reflection. This paper discusses the potential of computer-supported argument visualization tools for coping with the complexity of philosophical arguments. I will show, in particular, how the interactive and web-based argument mapping software “AGORA-net” can change the practice of philosophical reflection, communication, and collaboration. AGORA-net allows the graphical representation of complex argumentations in logical form and the synchronous and asynchronous collaboration on those “argument maps” (...)
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  49. Peter Lohmann & Heribert Vollmer (2013). Complexity Results for Modal Dependence Logic. Studia Logica 101 (2):343-366.score: 18.0
    Modal dependence logic was introduced recently by Väänänen. It enhances the basic modal language by an operator = (). For propositional variables p 1, . . . , p n , = (p 1, . . . , p n-1, p n ) intuitively states that the value of p n is determined by those of p 1, . . . , p n-1. Sevenster (J. Logic and Computation, 2009) showed that satisfiability for modal dependence logic is complete for nondeterministic (...)
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  50. Keith Morrison (2001). Simplicity and Complexity in Contemporary School Leadership: A Response to Grace. British Journal of Educational Studies 49 (4):379 - 385.score: 18.0
    Gerald Grace's (2000) paper Research and the Challenges of School Leadership: the Contribution of Critical Scholarship is applauded for making a powerful case for critical leadership studies to be taken seriously and for providing an exhortation for many educationists to think again about headship. However, this paper suggests that Grace's paper is weakened by:(a) traditionalism (e.g. a false equation of leadership with headship and neglect of more recent discourses of leadership, distributed leadership and complexity theory); (b) reductionism, oversimplification, selectivity (...)
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