Search results for 'modeling strategies' (try it on Scholar)

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  1. Marcel Weber (forthcoming). Experimental Modeling in Biology: In Vivo Representation and Stand-Ins As Modeling Strategies. Philosophy of Science.score: 108.0
    Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in (...)
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  2. Ehud Lamm (2013). Theoreticians as Professional Outsiders: The Modeling Strategies of John von Neumann and Norbert Wiener. In Oren Harman & Michael Dietrich (eds.), Outsider Scientists: Routes to Innovation in Biology. Chicago University Press.score: 108.0
    Both von Neumann and Wiener were outsiders to biology. Both were inspired by biology and both proposed models and generalizations that proved inspirational for biologists. Around the same time in the 1940s von Neumann developed the notion of self reproducing automata and Wiener suggested an explication of teleology using the notion of negative feedback. These efforts were similar in spirit. Both von Neumann and Wiener used mathematical ideas to attack foundational issues in biology, and the concepts they articulated had lasting (...)
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  3. Anya Plutynski (2006). Strategies of Model Building in Population Genetics. Philosophy of Science 73 (5):755-764.score: 108.0
    In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary (...)
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  4. Gérard G. Emch (2007). Models and the Dynamics of Theory-Building in Physics. Part I—Modeling Strategies. Studies in History and Philosophy of Science Part B 38 (3):558-585.score: 90.0
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  5. Emch Gérard G. (2007). Models and the Dynamics of Theory-Building in Physics. Part I—Modeling Strategies. Studies in History and Philosophy of Science Part B.score: 90.0
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  6. Marcel Boumans (2012). Modeling Strategies for Measuring Phenomena In-and Outside the Laboratory. In. In Henk W. de Regt (ed.), Epsa Philosophy of Science: Amsterdam 2009. Springer. 1--11.score: 90.0
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  7. Tomasz Smoleń & Adam Chuderski (2010). Modeling Strategies in Stroop with a General Architecture of Executive Control. In. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. 931--936.score: 90.0
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  8. Heinz Mandl, Cornelia Gräsel & Frank Fischer (2000). Problem-Oriented Learning: Facilitating the Use of Domain-Specific and Control Strategies Through Modeling by an Expert. In Walter J. Perrig & Alexander Grob (eds.), Control of Human Behavior, Mental Processes, and Consciousness: Essays in Honor of the 60th Birthday of August Flammer. Erlbaum. 165--182.score: 72.0
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  9. Susan Musante (2006). Strategies for Teaching Modeling to Students. Bioscience 56 (4):299.score: 72.0
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  10. D. M. Bailer-Jones (1999). Creative Strategies Employed in Modelling: A Case Study. [REVIEW] Foundations of Science 4 (4):375-388.score: 68.0
    This paper examines creative strategies employed inscientific modelling. It is argued that being creativepresents not a discrete event, but rather an ongoingeffort consisting of many individual `creative acts''.These take place over extended periods of time andcan be carried out by different people, working ondifferent aspects of the same project. The example ofextended extragalactic radio sources shows that, inorder to model a complicated phenomenon in itsentirety, the modelling task is split up into smallerproblems that result in several sub-models. This is (...)
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  11. Sergio Sismondo (1997). Modelling Strategies: Creating Autonomy for Biology's Theory of Games. History and Philosophy of the Life Sciences 19 (2):147 - 161.score: 68.0
    John Maynard Smith is the person most responsible for the use of game theory in evolutionary biology, having introduced and developed its major concepts, and later surveyed its uses. In this paper I look at some rhetorical work done by Maynard Smith and his co-author G.R. Price to make game theory a standard and common modelling tool for the evolutionary study of behavior. The original presentation of the ideas — in a 1973 Nature article — is frequently cited but almost (...)
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  12. Jonathan Opie (1998). Connectionist Modelling Strategies. Psycoloquy 9 (30).score: 63.0
    Green offers us two options: either connectionist models are literal models of brain activity or they are mere instruments, with little or no ontological significance. According to Green, only the first option renders connectionist models genuinely explanatory. I think there is a third possibility. Connectionist models are not literal models of brain activity, but neither are they mere instruments. They are abstract, IDEALISED models of the brain that are capable of providing genuine explanations of cognitive phenomena.
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  13. Dario Gregori, Lara Lusa, Rosalba Rosato & Luciano Silvestri (2008). Evaluating Effectiveness of Preoperative Testing Procedure: Some Notes on Modelling Strategies in Multi‐Centre Surveys. Journal of Evaluation in Clinical Practice 14 (1):11-18.score: 60.0
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  14. Rasmus Grønfeldt Winther, Michael J. Wade & Christopher C. Dimond (2013). Pluralism in Evolutionary Controversies: Styles and Averaging Strategies in Hierarchical Selection Theories. Biology and Philosophy 28 (6):957-979.score: 54.0
    Two controversies exist regarding the appropriate characterization of hierarchical and adaptive evolution in natural populations. In biology, there is the Wright–Fisher controversy over the relative roles of random genetic drift, natural selection, population structure, and interdemic selection in adaptive evolution begun by Sewall Wright and Ronald Aylmer Fisher. There is also the Units of Selection debate, spanning both the biological and the philosophical literature and including the impassioned group-selection debate. Why do these two discourses exist separately, and interact relatively little? (...)
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  15. Nicolas Fillion & Robert M. Corless (2014). On the Epistemological Analysis of Modeling and Computational Error in the Mathematical Sciences. Synthese 191 (7):1451-1467.score: 54.0
    Interest in the computational aspects of modeling has been steadily growing in philosophy of science. This paper aims to advance the discussion by articulating the way in which modeling and computational errors are related and by explaining the significance of error management strategies for the rational reconstruction of scientific practice. To this end, we first characterize the role and nature of modeling error in relation to a recipe for model construction known as Euler’s recipe. We then (...)
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  16. Ming Shan, Albert P. C. Chan, Yun Le & Yi Hu (forthcoming). Investigating the Effectiveness of Response Strategies for Vulnerabilities to Corruption in the Chinese Public Construction Sector. Science and Engineering Ethics:1-23.score: 54.0
    Response strategy is a key for preventing widespread corruption vulnerabilities in the public construction sector. Although several studies have been devoted to this area, the effectiveness of response strategies has seldom been evaluated in China. This study aims to fill this gap by investigating the effectiveness of response strategies for corruption vulnerabilities through a survey in the Chinese public construction sector. Survey data obtained from selected experts involved in the Chinese public construction sector were analyzed by factor analysis (...)
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  17. Michael E. Geisser Susan L. Murphy, Anna L. Kratz, David A. Williams (2012). The Association Between Symptoms, Pain Coping Strategies, and Physical Activity Among People with Symptomatic Knee and Hip Osteoarthritis. Frontiers in Psychology 3.score: 54.0
    Effective use of coping strategies by people with chronic pain conditions is associated with better functioning and adjustment to chronic disease. Although the effects of coping on pain have been well studied, less is known about how specific coping strategies relate to actual physical activity patterns in daily life. The purpose of this study was to evaluate how different coping strategies relate to symptoms and physical activity patterns in a sample of adults with knee and hip osteoarthritis (...)
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  18. James Justus (2005). Qualitative Scientific Modeling and Loop Analysis. Philosophy of Science 72 (5):1272-1286.score: 48.0
    Loop analysis is a method of qualitative modeling anticipated by Sewall Wright and systematically developed by Richard Levins. In Levins’ (1966) distinctions between modeling strategies, loop analysis sacrifices precision for generality and realism. Besides criticizing the clarity of these distinctions, Orzack and Sober (1993) argued qualitative modeling is conceptually and methodologically problematic. Loop analysis of the stability of ecological communities shows this criticism is unjustified. It presupposes an overly narrow view of qualitative modeling and underestimates (...)
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  19. John Symons (2008). A Computational Modeling Strategy for Levels. Philosophy of Science 75 (5):608-620.score: 46.0
    Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties (...)
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  20. Axel Gelfert (2013). Strategies of Model-Building in Condensed Matter Physics: Trade-Offs as a Demarcation Criterion Between Physics and Biology? Synthese 190 (2):253-272.score: 42.0
    This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more sophisticated (...)
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  21. William Goodwin, Global Climate Modeling as Applied Science.score: 42.0
    In this paper I argue that the appropriate analogy for “understanding what makes simulation results reliable” in Global Climate Modeling is not with scientific experimentation or measurement, but—at least in the case of the use of global climate models for policy development—with the applications of science in engineering design problems. The prospects for using this analogy to argue for the quantitative reliability of GCMs are assessed and compared with other potential strategies.
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  22. Collin Rice & Joshua Smart (2011). Interdisciplinary Modeling: A Case Study of Evolutionary Economics. Biology and Philosophy 26 (5):655-675.score: 42.0
    Biologists and economists use models to study complex systems. This similarity between these disciplines has led to an interesting development: the borrowing of various components of model-based theorizing between the two domains. A major recent example of this strategy is economists’ utilization of the resources of evolutionary biology in order to construct models of economic systems. This general strategy has come to be called evolutionary economics and has been a source of much debate among economists. Although philosophers have developed literatures (...)
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  23. Werner Ehm (2005). Meta-Analysis O Mind-Matter Experiments: A Statistical Modeling Perspective. Mind and Matter 3 (1):85-132.score: 42.0
    Are there relationships between consciousness and the material world? Empirical evidence for such a connection was reported in several meta-analyses of mind-matter experiments designed to address this question. In this paper we consider such meta-analyses from a statistical modeling perspective, emphasizing strategies to validate the models and the associated statistical procedures. In particular, we explicitly model increased data variability and selection mechanisms, which permits us to estimate 'selection profiles ' and to reassess the experimental effect in view of (...)
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  24. Richard C. Schugart (2010). Mathematical Modeling in Wound Healing, Bone Regeneration and Tissue Engineering. Acta Biotheoretica 58 (4):355-367.score: 42.0
    The processes of wound healing and bone regeneration and problems in tissue engineering have been an active area for mathematical modeling in the last decade. Here we review a selection of recent models which aim at deriving strategies for improved healing. In wound healing, the models have particularly focused on the inflammatory response in order to improve the healing of chronic wound. For bone regeneration, the mathematical models have been applied to design optimal and new treatment strategies (...)
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  25. Richard A. Depue & Jeannine V. Morrone-Strupinsky (2005). Modeling Human Behavioral Traits and Clarifying the Construct of Affiliation and its Disorders. Behavioral and Brain Sciences 28 (3):371-378.score: 42.0
    Commentary on our target article centers around six main topics: (1) strategies in modeling the neurobehavioral foundation of human behavioral traits; (2) clarification of the construct of affiliation; (3) developmental aspects of affiliative bonding; (4) modeling disorders of affiliative reward; (5) serotonin and affiliative behavior; and (6) neural considerations. After an initial important research update in section R1, our Response is organized around these topics in the following six sections, R2 to R7.
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  26. Giovanni Pezzulo & Haris Dindo (2013). Intentional Strategies That Make Co-Actors More Predictable: The Case of Signaling. Behavioral and Brain Sciences 36 (4):371-372.score: 42.0
    Pickering & Garrod (P&G) explain dialogue dynamics in terms of forward modeling and prediction-by-simulation mechanisms. Their theory dissolves a strict segregation between production and comprehension processes, and it links dialogue to action-based theories of joint action. We propose that the theory can also incorporate intentional strategies that increase communicative success: for example, signaling strategies that help remaining predictable and forming common ground.
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  27. Jorge Luis Orozco Pérez, Oscar Atiénzar Rodríguez & Maritza Cuenca Díaz (2013). Methodological strategy for the direction of the educational process for the development of intellectual skill modeling. Humanidades Médicas 13 (1):139-156.score: 40.0
    El artículo muestra una estrategia metodológica para garantizar la dirección del proceso educativo para el desarrollo de la habilidad intelectual modelación en los estudiantes; devela sus principales fundamentos epistémicos, sus etapas y acciones esenciales. Para ello se aplicaron métodos científicos de investigación. La constatación de los resultados brinda evidencias positivas acerca de su pertinencia, al considerar el carácter coparticipativo y coprotagónico que adquieren las influencias educativas en el contexto institucional en la dirección de un proceso educativo único. The article shows (...)
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  28. William Bechtel & Adele A. Abrahamsen (2013). Thinking Dynamically About Biological Mechanisms: Networks of Coupled Oscillators. [REVIEW] Foundations of Science 18 (4):707-723.score: 36.0
    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 (...)
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  29. Rosanna Keefe (2012). Modelling Vagueness: What Can We Ignore? Philosophical Studies 161 (3):453-470.score: 36.0
    A theory of vagueness gives a model of vague language and of reasoning within the language. Among the models that have been offered are Degree Theorists’ numerical models that assign values between 0 and 1 to sentences, rather than simply modelling sentences as true or false. In this paper, I ask whether we can benefit from employing a rich, well-understood numerical framework, while ignoring those aspects of it that impute a level of mathematical precision that is not present in the (...)
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  30. John Stewart & Olivier Gapenne (2004). Reciprocal Modelling of Active Perception of 2-D Forms in a Simple Tactile-Vision Substitution System. Minds and Machines 14 (3):309-330.score: 36.0
    The strategies of action employed by a human subject in order to perceive simple 2-D forms on the basis of tactile sensory feedback have been modelled by an explicit computer algorithm. The modelling process has been constrained and informed by the capacity of human subjects both to consciously describe their own strategies, and to apply explicit strategies; thus, the strategies effectively employed by the human subject have been influenced by the modelling process itself. On this basis, (...)
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  31. Elske Vaart & Charlotte K. Hemelrijk (2012). 'Theory of Mind' in Animals: Ways to Make Progress. Synthese (3):1-20.score: 36.0
    Whether any non-human animal can attribute mental states to others remains the subject of extensive debate. This despite the fact that several species have behaved as if they have a ‘theory of mind’ in various behavioral tasks. In this paper, we review the reasons of skeptics for their doubts: That existing experimental setups cannot distinguish between ‘mind readers’ and ‘behavior readers’, that results that seem to indicate ‘theory of mind’ may come from studies that are insufficiently controlled, and that our (...)
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  32. Dae-Shik Kim Jun-Cheol Park, Jae Hyun Lim, Hansol Choi (2012). Predictive Coding Strategies for Developmental Neurorobotics. Frontiers in Psychology 3.score: 36.0
    In recent years, predictive coding strategies have been proposed as a possible way of how the brain might make sense of the truly overwhelming amount of sensory data available to the brain at any given moment of time. Instead of the raw data, the brain is hypothesized to guide its actions by assigning causal believes to the observed error between what it expected to happen, and what actually happens. In this paper we present a potpourri of developmental neurorobotics experiments (...)
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  33. Elske van der Vaart & Charlotte K. Hemelrijk (2012). 'Theory of Mind' in Animals: Ways to Make Progress. Synthese 191 (3):1-20.score: 36.0
    Whether any non-human animal can attribute mental states to others remains the subject of extensive debate. This despite the fact that several species have behaved as if they have a ‘theory of mind’ in various behavioral tasks. In this paper, we review the reasons of skeptics for their doubts: That existing experimental setups cannot distinguish between ‘mind readers’ and ‘behavior readers’, that results that seem to indicate ‘theory of mind’ may come from studies that are insufficiently controlled, and that our (...)
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  34. Catherine Gunzenhauser, Anika Faesche, Wolfgang Friedlmeier & Antje von Suchodoletz (2013). Face It or Hide It: Parental Socialization of Reappraisal and Response Suppression. Frontiers in Psychology 4:992.score: 36.0
    Mastery of cognitive emotion regulation strategies is an important developmental task. This paper focuses on two strategies that occur from preschool age onwards (Stegge & Meerum Terwogt, 2007): reappraisal and response suppression. Parental socialization of these strategies was investigated in a sample of N = 219 parents and their children. Informed by the tripartite model of family impact on children’s emotion regulation, direct relations of emotion socialization processes (modeling and reactions to the child’s negative emotions) and (...)
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  35. Matthew Mayhew & Patricia King (2008). How Curricular Content and Pedagogical Strategies Affect Moral Reasoning Development in College Students. Journal of Moral Education 37 (1):17-40.score: 32.0
    College instructors use a variety of approaches to teach students to reason more effectively about issues with a moral dimension and achieve mixed results. This pre?post study of 423 undergraduate students examined the effects of morally explicit and implicit curricular content and of selected pedagogical strategies on moral reasoning development. Using causal modelling to control for a range of student background variables as well as Time 1 scores, 52% of the variance in moral reasoning scores was explained; we found (...)
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  36. Jeffrey C. Schank (2001). Dimensions of Modelling: Generality and Integrativeness. Behavioral and Brain Sciences 24 (6):1075-1076.score: 32.0
    Webb has articulated a clear, multi-dimensional framework for discussing simulation models and modelling strategies. This framework will likely co-evolve with modelling. As such, it will be important to continue to clarify these dimensions and perhaps add to them. I discuss the dimension of generality and suggest that a dimension of integrativeness may also be needed.
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  37. Richard Levins (2006). Strategies of Abstraction. Biology and Philosophy 21 (5):741-755.score: 30.0
    Abstraction is seen as an active process which both enlightens and obscures. Abstractions are not true or false but relatively enlightening or obscuring according to the problem under study; different abstractions may grasp different aspects of a problem. Abstractions may be useless if they can answer questions only about themselves. A theoretical enterprise explores reality through acluster of abstractions that use different perspectives, temporal and horizontal scales, and assumes different givens.
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  38. Michael A. Arbib & James Bonaiuto (2007). From Grasping to Complex Imitation: Mirror Systems on the Path to Language. Mind and Society 7 (1):43-64.score: 30.0
    We focus on the evolution of action capabilities which set the stage for language, rather than analyzing how further brain evolution built on these capabilities to yield a language-ready brain. Our framework is given by the Mirror System Hypothesis, which charts a progression from a monkey-like mirror neuron system (MNS) to a chimpanzee-like mirror system that supports simple imitation and thence to a human-like mirror system that supports complex imitation and language. We present the MNS2 model, a new model of (...)
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  39. Marc D. Lewis (2005). An Emerging Dialogue Among Social Scientists and Neuroscientists on the Causal Bases of Emotion. Behavioral and Brain Sciences 28 (2):223-234.score: 30.0
    The target article developed a dynamic systems framework that viewed the causal basis of emotion as a self-organizing process giving rise to cognitive appraisal concurrently. Commentators on the article evaluated this framework and the principles and mechanisms it incorporated. They also suggested additional principles, mechanisms, modeling strategies, and phenomena related to emotion and appraisal, in place of or extending from those already proposed. There was general agreement that nonlinear causal processes are fundamental to the psychology and neurobiology of (...)
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  40. Raphael Scholl & Tim Räz (2013). Modeling Causal Structures. European Journal for Philosophy of Science 3 (1):115-132.score: 30.0
    The Lotka–Volterra predator-prey-model is a widely known example of model-based science. Here we reexamine Vito Volterra’s and Umberto D’Ancona’s original publications on the model, and in particular their methodological reflections. On this basis we develop several ideas pertaining to the philosophical debate on the scientific practice of modeling. First, we show that Volterra and D’Ancona chose modeling because the problem in hand could not be approached by more direct methods such as causal inference. This suggests a philosophically insightful (...)
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  41. Giovanni Barosi, Lorenzo Magnani & Mario Stefanelli (1993). Medical Diagnostic Reasoning: Epistemological Modeling as a Strategy for Design of Computer-Based Consultation Programs. Theoretical Medicine and Bioethics 14 (1).score: 30.0
    The complexity of cognitive emulation of human diagnostic reasoning is the major challenge in the implementation of computer-based programs for diagnostic advice in medicine. We here present an epistemological model of diagnosis with the ultimate goal of defining a high-level language for cognitive and computational primitives. The diagnostic task proceeds through three different phases: hypotheses generation, hypotheses testing and hypotheses closure. Hypotheses generation has the inferential form of abduction (from findings to hypotheses) constrained under the criterion of plausibility. Hypotheses testing (...)
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  42. Ulrich Krohs & Werner Callebaut (2007). Data Without Models Merging with Models Without Data. In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. 181--213.score: 30.0
    Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...)
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  43. Christian Haak (2002). The History of Models. Does It Matter? Mind and Society 3 (1):33-41.score: 30.0
    This paper investigates the justification of the concept of a balance of nature in population ecology as a case of model based reasoning. The ecologist A.J. Nicholson understood balance as an outcome of intraspecific competition in populations. His models implied density dependent growth of populations oscillating around an equilibrium state. Today the assumption of density dependence is tested statistically by using models that represent certain data dynamics. This however, does not test for density dependence in the sense suggested by Nicholson. (...)
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  44. Jonathan Perraton (2011). Explaining Growth? The Case of the Trade–Growth Relationship. Journal of Economic Methodology 18 (3):283-296.score: 30.0
    This paper provides a critical analysis of the modelling strategies adopted in the trade?growth literature. Despite a huge number of econometric studies, there is a growing dissatisfaction with such studies and serious questions over what exactly has been learnt from them. Econometric work has been criticized for, amongst other things, its lack of clear relationship to underlying theory and questionable use of proxies for trade policy. It is frequently unclear what hypothesis is being tested in this literature. Universalist assumptions (...)
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  45. Ç Gülçiçek & B. Güneş (2004). Materializing the Concepts During Science Instruction: Modeling Strategy, Computer Simulations and Analogies. Science and Education 29 (134):36-48.score: 30.0
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  46. Margaret Morrison (2009). Models, Measurement and Computer Simulation: The Changing Face of Experimentation. Philosophical Studies 143 (1):33 - 57.score: 28.0
    The paper presents an argument for treating certain types of computer simulation as having the same epistemic status as experimental measurement. While this may seem a rather counterintuitive view it becomes less so when one looks carefully at the role that models play in experimental activity, particularly measurement. I begin by discussing how models function as “measuring instruments” and go on to examine the ways in which simulation can be said to constitute an experimental activity. By focussing on the connections (...)
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  47. John S. Fenlon, Malcolm J. Faddy, Menia Toussidou & Michael E. Courcy Williamdes (forthcoming). Egg Distributions of Insect Parasitoids: Modelling and Analysis of Temporal Data with Host Density Dependence. Acta Biotheoretica.score: 28.0
    A simple numerical procedure is presented for the problem of estimating the parameters of models for the distribution of eggs oviposited in a host. The modelling is extended to incorporate both host density and time dependence to produce a remarkably parsimonious structure with only seven parameters to describe a data set of over 3,000 observations. This is further refined using a mixed model to accommodate several large outliers. Both models show that the level of superparasitism declines with increasing host density, (...)
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  48. Johanna M. Harte & Pieter Koele (2001). Modelling and Describing Human Judgement Processes: The Multiattribute Evaluation Case. Thinking and Reasoning 7 (1):29 – 49.score: 28.0
    In this article we describe research methods that are used for the study of individual multiattribute evaluation processes. First we explain that a multiattribute evaluation problem involves the evaluation of a set of alternatives, described by their values on a number of alternatives. We discuss a number of evaluation strategies that may be applied to arrive at a conclusion about the attractiveness or suitability of the alternatives, and next introduce two main research paradigms in this area, structural modelling and (...)
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  49. Sieuwert van Otterloo, Wiebe Van Der Hoek & Michael Wooldridge (2006). Knowledge Condition Games. Journal of Logic, Language and Information 15 (4):425-452.score: 28.0
    Understanding the flow of knowledge in multi-agent protocols is essential when proving the correctness or security of such protocols. Current logical approaches, often based on model checking, are well suited for modeling knowledge in systems where agents do not act strategically. Things become more complicated in strategic settings. In this paper we show that such situations can be understood as a special type of game – a knowledge condition game – in which a coalition “wins” if it is able (...)
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