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William Bechtel [129]William P. Bechtel [52]
  1. William Bechtel & Robert C. Richardson (1993). Discovering Complexity Decomposition and Localization as Strategies in Scientific Research. Monograph Collection (Matt - Pseudo).
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  2. William Bechtel (2005). Explanation: A Mechanist Alternative. Studies in History and Philosophy of Biol and Biomed Sci 36 (2):421--441.
    Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ dia- grams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations (...)
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  3.  42
    Arnon Levy & William Bechtel (2013). Abstraction and the Organization of Mechanisms. Philosophy of Science 80 (2):241-261.
  4. Carl F. Craver & William Bechtel (2007). Top-Down Causation Without Top-Down Causes. Biology and Philosophy 22 (4):547-563.
    We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...)
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  5.  88
    William P. Bechtel (1988). Philosophy of Mind: An Overview for Cognitive Science. Lawrence Erlbaum.
    Specifically designed to make the philosophy of mind intelligible to those not trained in philosophy, this book provides a concise overview for students and researchers in the cognitive sciences. Emphasizing the relevance of philosophical work to investigations in other cognitive sciences, this unique text examines such issues as the meaning of language, the mind-body problem, the functionalist theories of cognition, and intentionality. As he explores the philosophical issues, Bechtel draws connections between philosophical views and theoretical and experimental work (...)
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  6.  6
    William Bechtel (2015). Can Mechanistic Explanation Be Reconciled with Scale-Free Constitution and Dynamics? Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 53:84-93.
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  7. William Bechtel (2007). Discovering Cell Mechanisms: The Creation of Modern Cell Biology. Journal of the History of Biology 40 (1):185-187.
    Between 1940 and 1970 pioneers in the new field of cell biology discovered the operative parts of cells and their contributions to cell life. They offered mechanistic accounts that explained cellular phenomena by identifying the relevant parts of cells, the biochemical operations they performed, and the way in which these parts and operations were organised to accomplish important functions. Cell biology was a revolutionary science but in this book it also provides fuel for yet another revolution, one that focuses on (...)
     
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  8. William Bechtel (2011). Mechanism and Biological Explanation. Philosophy of Science 78 (4):533-557.
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  9. William Bechtel & Adele Abrahamsen (2010). Dynamic Mechanistic Explanation: Computational Modeling of Circadian Rhythms as an Exemplar for Cognitive Science. Studies in History and Philosophy of Science Part A 41 (3):321-333.
    Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their (...)
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  10. William P. Bechtel & Jennifer Mundale (1999). Multiple Realizability Revisited: Linking Cognitive and Neural States. Philosophy of Science 66 (2):175-207.
    The claim of the multiple realizability of mental states by brain states has been a major feature of the dominant philosophy of mind of the late 20th century. The claim is usually motivated by evidence that mental states are multiply realized, both within humans and between humans and other species. We challenge this contention by focusing on how neuroscientists differentiate brain areas. The fact that they rely centrally on psychological measures in mapping the brain and do so in a comparative (...)
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  11.  19
    William Bechtel & Oron Shagrir (2015). The Non‐Redundant Contributions of Marr's Three Levels of Analysis for Explaining Information‐Processing Mechanisms. Topics in Cognitive Science 7 (2):312-322.
    Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform. The representation and algorithmic perspective offers an understanding of how information about the environment is (...)
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  12. David M. Kaplan & William Bechtel (2011). Dynamical Models: An Alternative or Complement to Mechanistic Explanations? Topics in Cognitive Science 3 (2):438-444.
    Abstract While agreeing that dynamical models play a major role in cognitive science, we reject Stepp, Chemero, and Turvey's contention that they constitute an alternative to mechanistic explanations. We review several problems dynamical models face as putative explanations when they are not grounded in mechanisms. Further, we argue that the opposition of dynamical models and mechanisms is a false one and that those dynamical models that characterize the operations of mechanisms overcome these problems. By briefly considering (...)
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  13.  2
    David Pickles, William Bechtel & Adele Abrahamson (1992). Connectionism and the Mind: An Introduction to Parallel Processing in Networks. Philosophical Quarterly 42 (166):101.
  14. William Bechtel & Adele A. Abrahamsen (2013). Thinking Dynamically About Biological Mechanisms: Networks of Coupled Oscillators. [REVIEW] Foundations of Science 18 (4):707-723.
    Explaining the complex dynamics exhibited in many biological mechanisms requires extending the recent philosophical treatment of mechanisms that emphasizes sequences of operations. To understand how nonsequentially organized mechanisms will behave, scientists often advance what we call dynamic mechanistic explanations. These begin with a decomposition of the mechanism into component parts and operations, using a variety of laboratory-based strategies. Crucially, the mechanism is then recomposed by means of computational models in which variables or terms in differential equations correspond to properties of (...)
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  15. William Bechtel (2013). From Molecules to Behavior and the Clinic: Integration in Chronobiology. Studies in History and Philosophy of Science Part C 44 (4):493-502.
    Chronobiology, especially the study of circadian rhythms, provides a model scientific field in which philosophers can study how investigators from a variety of disciplines working at different levels of organization are each contributing to a multi-level account of the responsible mechanism. I focus on how the framework of mechanistic explanation integrates research designed to decompose the mechanism with efforts directed at recomposition that relies especially on computation models. I also examine how recently the integration has extended beyond basic research (...)
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  16. William Bechtel (2009). Looking Down, Around, and Up: Mechanistic Explanation in Psychology. Philosophical Psychology 22 (5):543-564.
    Accounts of mechanistic explanation have emphasized the importance of looking down—decomposing a mechanism into its parts and operations. Using research on visual processing as an exemplar, I illustrate how productive such research has been. But once multiple components of a mechanism have been identified, researchers also need to figure out how it is organized—they must look around and determine how to recompose the mechanism. Although researchers often begin by trying to recompose the mechanism in terms of sequential operations, they frequently (...)
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  17.  80
    Mitchell Herschbach & William Bechtel (2014). Mental Mechanisms and Psychological Construction. In Lisa Feldman Barrett & James Russell (eds.), The Psychological Construction of Emotion. Guilford Press 21-44.
  18. William Bechtel & Cory D. Wright (2009). What is Psychological Explanation? In P. Calvo & J. Symons (eds.), Routledge Companion to the Philosophy of Psychology. Routledge 113--130.
    Due to the wide array of phenomena that are of interest to them, psychologists offer highly diverse and heterogeneous types of explanations. Initially, this suggests that the question "What is psychological <span class='Hi'>explanation</span>?" has no single answer. To provide appreciation of this diversity, we begin by noting some of the more common types of explanations that psychologists provide, with particular focus on classical examples of explanations advanced in three different areas of psychology: psychophysics, physiological psychology, and information-processing psychology. To analyze (...)
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  19. William P. Bechtel (1994). Levels of Description and Explanation in Cognitive Science. Minds and Machines 4 (1):1-25.
    The notion of levels has been widely used in discussions of cognitive science, especially in discussions of the relation of connectionism to symbolic modeling of cognition. I argue that many of the notions of levels employed are problematic for this purpose, and develop an alternative notion grounded in the framework of mechanistic explanation. By considering the source of the analogies underlying both symbolic modeling and connectionist modeling, I argue that neither is likely to provide an adequate analysis of processes at (...)
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  20. William Bechtel (2009). Generalization and Discovery by Assuming Conserved Mechanisms: Cross‐Species Research on Circadian Oscillators. Philosophy of Science 76 (5):762-773.
    In many domains of biology, explanation takes the form of characterizing the mechanism responsible for a particular phenomenon in a specific biological system. How are such explanations generalized? One important strategy assumes conservation of mechanisms through evolutionary descent. But conservation is seldom complete. In the case discussed, the central mechanism for circadian rhythms in animals was first identified in Drosophila and then extended to mammals. Scientists' working assumption that the clock mechanisms would be conserved both yielded important generalizations and served (...)
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  21. William Bechtel (2010). The Downs and Ups of Mechanistic Research: Circadian Rhythm Research as an Exemplar. [REVIEW] Erkenntnis 73 (3):313 - 328.
    In the context of mechanistic explanation, reductionistic research pursues a decomposition of complex systems into their component parts and operations. Using research on the mechanisms responsible for circadian rhythms, I consider both the gains that have been made by discovering genes and proteins that figure in these intracellular oscillators and also highlight the increasingly recognized need to understand higher-level integration, both between cells in the central oscillator and between the central and peripheral oscillators. This history illustrates a common need to (...)
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  22.  15
    Sara Green, Arnon Levy & William Bechtel (2015). Design Sans Adaptation. European Journal for Philosophy of Science 5 (1):15-29.
    Design thinking in general, and optimality modeling in particular, have traditionally been associated with adaptationism—a research agenda that gives pride of place to natural selection in shaping biological characters. Our goal is to evaluate the role of design thinking in non-evolutionary analyses. Specifically, we focus on research into abstract design principles that underpin the functional organization of extant organisms. Drawing on case studies from engineering-inspired approaches in biology we show how optimality analysis, and other design-related methods, play a specific methodological (...)
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  23. William Bechtel, Robert C. Richardson & Scott A. Kleiner (1996). Discovering Complexity. History and Philosophy of the Life Sciences 18 (3):363-382.
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  24. William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.) (2001). Philosophy and the Neurosciences: A Reader. Blackwell.
    2. Daugman, J. G. Brain metaphor and brain theory 3. Mundale, J. Neuroanatomical Foundations of Cognition: Connecting the Neuronal Level with the Study of Higher Brain Areas.
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  25. William Bechtel (2001). Linking Cognition and Brain: The Cognitive Neuroscience of Language. In William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.), Philosophy and the Neurosciences: A Reader. Blackwell
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  26. William Bechtel & Adele Abrahamsen (2002). Connectionism and the Mind: Parallel Processing, Dynamics, and Evolution in Networks. Wiley-Blackwell.
     
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  27. Cory D. Wright & William P. Bechtel (2007). Mechanisms and Psychological Explanation. In Paul Thagard (ed.), Philosophy of Psychology and Cognitive Science. Elsevier
    As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather (...)
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  28. William P. Bechtel (2005). The Challenge of Characterizing Operations in the Mechanisms Underlying Behavior. Journal of the Experimental Analysis of Behavior 84:313-325.
    Neuroscience and cognitive science seek to explain behavioral regularities in terms of underlying mechanisms. An important element of a mechanistic explanation is a characterization of the operations of the parts of the mechanism. The challenge in characterizing such operations is illustrated by an example from the history of physiological chemistry in which some investigators tried to characterize the internal operations in the same terms as the overall physiological system while others appealed to elemental chemistry. In order for biochemistry to become (...)
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  29. William Bechtel (2007). Top-Down Causation Without Top-Down Causes. Biology and Philosophy 22 (4):547-563.
  30. William Bechtel & Adele Abrahamsen, Complex Biological Mechanisms: Cyclic, Oscillatory, and Autonomous.
    The mechanistic perspective has dominated biological disciplines such as biochemistry, physiology, cell and molecular biology, and neuroscience, especially during the 20th century. The primary strategy is reductionist: organisms are to be decomposed into component parts and operations at multiple levels. Researchers adopting this perspective have generated an enormous body of information about the mechanisms of life at scales ranging from the whole organism down to genetic and other molecular operations.
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  31. William P. Bechtel (1998). Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science. Cognitive Science 22 (3):295-317.
    Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...)
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  32. William Bechtel (2007). Reducing Psychology While Maintaining its Autonomy Via Mechanistic Explanations. In M. Schouten & H. L. De Joong (eds.), The Matter of the Mind: Philosophical Essays on Psychology, Neuroscience and Reduction. Blackwell Publishing
    Arguments for the autonomy of psychology or other higher-level sciences have often taken the form of denying the possibility of reduction. The form of reduction most proponents and critics of the autonomy of psychology have in mind is theory reduction. Mechanistic explanations provide a different perspective. Mechanistic explanations are reductionist insofar as they appeal to lower-level entities—the component parts of a mechanism and their operations— to explain a phenomenon. However, unlike theory reductions, mechanistic explanations also recognize the fundamental role of (...)
     
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  33.  38
    William Bechtel (forthcoming). Investigating Neural Representations: The Tale of Place Cells. Synthese:1-35.
    While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving (...)
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  34. William Bechtel & Adele Abrahamsen (1991). Connectionism and the Mind. Wiley-Blackwell.
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  35. William Bechtel (2010). The Cell: Locus or Object of Inquiry? Studies in History and Philosophy of Science Part C 41 (3):172-182.
    Research in many fields of biology has been extremely successful in decomposing biological mechanisms to discover their parts and operations. It often remains a significant challenge for scientists to recompose these mechanisms to understand how they function as wholes and interact with the environments around them. This is true of the eukaryotic cell. Although initially identified in nineteenth-century cell theory as the fundamental unit of organisms, researchers soon learned how to decompose it into its organelles and chemical constituents and have (...)
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  36. William Bechtel (2013). From Molecules to Networks: Adoption of Systems Approaches in Circadian Rhythm Research. In Hanne Andersen, Dennis Dieks, Wenceslao González, Thomas Uebel & Gregory Wheeler (eds.), New Challenges to Philosophy of Science. Springer Verlag 211--223.
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  37. William Bechtel (2012). Identity, Reduction, and Conserved Mechanisms: Perspectives From Circadian Rhythm Research. In Hill Christopher & Gozzano Simone (eds.), New Perspectives on Type Identity: The Mental and the Physical. Cambridge University Press 43.
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  38. William Bechtel & Adele Abrahamsen (2009). Decomposing, Recomposing, and Situating Circadian Mechanisms: Three Tasks in Developing Mechanistic Explanations. In H. Leitgeb & A. Hieke (eds.), Reduction: Between the Mind and the Brain. Ontos 12--177.
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  39. William P. Bechtel (2002). Decomposing the Brain: A Long Term Pursuit. [REVIEW] Brain and Mind 3 (1):229-242.
    This paper defends cognitive neuroscience’s project of developing mechanistic explan- ations of cognitive processes through decomposition and localization against objections raised by William Uttal in The New Phrenology. The key issue between Uttal and researchers pursuing cognitive neuroscience is that Uttal bets against the possibility of decomposing mental operations into component elementary operations which are localized in distinct brain regions. The paper argues that it is through advancing and revising what are likely to be overly simplistic and incorrect decompositions that (...)
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  40. William Bechtel (2009). Constructing a Philosophy of Science of Cognitive Science. Trends in Cognitive Sciences 1 (3):548-569.
    Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science needs an account of (...)
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  41. William Bechtel (2007). Mental Mechanisms: Philosophical Perspectives on Cognitive Neuroscience. Psychology Press.
    A variety of scientific disciplines have set as their task explaining mental activities, recognizing that in some way these activities depend upon our brain. But, until recently, the opportunities to conduct experiments directly on our brains were limited. As a result, research efforts were split between disciplines such as cognitive psychology, linguistics, and artificial intelligence that investigated behavior, while disciplines such as neuroanatomy, neurophysiology, and genetics experimented on the brains of non-human animals. In recent decades these disciplines integrated, and (...)
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  42. William P. Bechtel (forthcoming). The Epistemology of Evidence in Cognitive Neuroscience. In R. Skipper Jr, C. Allen, R. A. Ankeny, C. F. Craver, L. Darden, G. Mikkelson & and R. Richardson (eds.), Philosophy and the Life Sciences: A Reader. MIT Press
    It is no secret that scientists argue. They argue about theories. But even more, they argue about the evidence for theories. Is the evidence itself trustworthy? This is a bit surprising from the perspective of traditional empiricist accounts of scientific methodology according to which the evidence for scientific theories stems from observation, especially observation with the naked eye. These accounts portray the testing of scientific theories as a matter of comparing the predictions of the theory with the data generated by (...)
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  43. William P. Bechtel (2001). Decomposing and Localizing Vision: An Exemplar for Cognitive Neuroscience. In William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.), Philosophy and the Neurosciences: A Reader. Blackwell 225--249.
  44. William Bechtel (2001). Representations: From Neural Systems to Cognitive Systems. In William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.), Philosophy and the Neurosciences: A Reader. Blackwell
  45.  5
    Daniel C. Burnston, Benjamin Sheredos, Adele Abrahamsen & William Bechtel (2014). Scientists’ Use of Diagrams in Developing Mechanistic Explanations: A Case Study From Chronobiology. Pragmatics and Cognition 22 (2):224-243.
  46. William Bechtel (2007). In Search of Mitochondrial Mechanisms: Interfield Excursions Between Cell Biology and Biochemistry. Journal of the History of Biology 40 (1):1 - 33.
    Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to (...)
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  47. William P. Bechtel, Mental Mechanisms: What Are the Operations?
    trying to explain these reactions in terms of changes in ele- began trying to characterize physiological processes in.
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  48. George Graham & William Bechtel (eds.) (1998). A Companion to Cognitive Science. Blackwell.
     
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  49. William Bechtel & Adele Abrahamsen (2008). From Reduction Back to Higher Levels. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society 559--564.
  50.  21
    William Bechtel (2012). Understanding Endogenously Active Mechanisms: A Scientific and Philosophical Challenge. [REVIEW] European Journal for Philosophy of Science 2 (2):233-248.
    Abstract Although noting the importance of organization in mechanisms, the new mechanistic philosophers of science have followed most biologists in focusing primarily on only the simplest mode of organization in which operations are envisaged as occurring sequentially. Increasingly, though, biologists are recognizing that the mechanisms they confront are non-sequential and the operations nonlinear. To understand how such mechanisms function through time, they are turning to computational models and tools of dynamical systems theory. Recent research on circadian rhythms addressing both intracellular (...)
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