Results for 'finite models'

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  1. The Concept of Truth in a Finite Universe.Panu Raatikainen - 2000 - Journal of Philosophical Logic 29 (6):617-633.
    The prospects and limitations of defining truth in a finite model in the same language whose truth one is considering are thoroughly examined. It is shown that in contradistinction to Tarski's undefinability theorem for arithmetic, it is in a definite sense possible in this case to define truth in the very language whose truth is in question.
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  2.  94
    Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - manuscript
    For computer simulation models to usefully inform climate risk management decisions, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that need less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and extent of uncertainty quantification. Seeing (...)
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  3.  37
    Does the Principle of Compositionality Explain Productivity? For a Pluralist View of the Role of Formal Languages as Models.Ernesto Perini-Santos - 2017 - Contexts in Philosophy 2017 - CEUR Workshop Proceedings.
    One of the main motivations for having a compositional semantics is the account of the productivity of natural languages. Formal languages are often part of the account of productivity, i.e., of how beings with finite capaci- ties are able to produce and understand a potentially infinite number of sen- tences, by offering a model of this process. This account of productivity con- sists in the generation of proofs in a formal system, that is taken to represent the way speakers (...)
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  4. No Rationality Through Brute-Force.Danilo Fraga Dantas - 2017 - Filosofia Unisinos 18 (3):195-200.
    All reasoners described in the most widespread models of a rational reasoner exhibit logical omniscience, which is impossible for finite reasoners (real reasoners). The most common strategy for dealing with the problem of logical omniscience is to interpret the models using a notion of beliefs different from explicit beliefs. For example, the models could be interpreted as describing the beliefs that the reasoner would hold if the reasoner were able reason indefinitely (stable beliefs). Then the (...) would describe maximum rationality, which a finite reasoner can only approach in the limit of a reasoning sequence. This strategy has important consequences for epistemology. If a finite reasoner can only approach maximum rationality in the limit of a reasoning sequence, then the efficiency of reasoning is epistemically (and not only pragmatically) relevant. In this paper, I present an argument to this conclusion and discuss its consequences, as, for example, the vindication of the principle 'no rationality through brute-force'. (shrink)
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  5.  75
    Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal (...) provide understanding misguided? In this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)
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  6. Model Organisms Are Not Models.Arnon Levy & Adrian Currie - 2015 - British Journal for the Philosophy of Science 66 (2):327-348.
    Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different (...)
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  7. Confirmation and Robustness of Climate Models.Elisabeth A. Lloyd - 2010 - Philosophy of Science 77 (5):971–984.
    Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, (...)
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  8. Models as Make-Believe: Imagination, Fiction, and Scientific Representation.Adam Toon - 2012 - Palgrave-Macmillan.
    Models as Make-Believe offers a new approach to scientific modelling by looking to an unlikely source of inspiration: the dolls and toy trucks of children's games of make-believe.
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  9. Climate Models, Calibration, and Confirmation.Katie Steele & Charlotte Werndl - 2013 - British Journal for the Philosophy of Science 64 (3):609-635.
    We argue that concerns about double-counting—using the same evidence both to calibrate or tune climate models and also to confirm or verify that the models are adequate—deserve more careful scrutiny in climate modelling circles. It is widely held that double-counting is bad and that separate data must be used for calibration and confirmation. We show that this is far from obviously true, and that climate scientists may be confusing their targets. Our analysis turns on a Bayesian/relative-likelihood approach to (...)
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  10.  29
    Non-Deterministic Algebraization of Logics by Swap Structures.Marcelo E. Coniglio, Aldo Figallo-Orellano & Ana Claudia Golzio - forthcoming - Logic Journal of the IGPL.
    Multialgebras (or hyperalgebras or non-deterministic algebras) have been much studied in mathematics and in computer science. In 2016 Carnielli and Coniglio introduced a class of multialgebras called swap structures, as a semantic framework for dealing with several Logics of Formal Inconsistency (or LFIs) that cannot be semantically characterized by a single finite matrix. In particular, these LFIs are not algebraizable by the standard tools of abstract algebraic logic. In this paper, the first steps towards a theory of non-deterministic algebraization (...)
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  11.  94
    MISSing the World: Models as Isolations, Representations, and Credible Worlds.Uskali Mäki - 2009 - Erkenntnis 70 (1):29-43.
    This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), and (...)
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  12. An Introduction to Partition Logic.David Ellerman - 2014 - Logic Journal of the IGPL 22 (1):94-125.
    Classical logic is usually interpreted as the logic of propositions. But from Boole's original development up to modern categorical logic, there has always been the alternative interpretation of classical logic as the logic of subsets of any given (nonempty) universe set. Partitions on a universe set are dual to subsets of a universe set in the sense of the reverse-the-arrows category-theoretic duality--which is reflected in the duality between quotient objects and subobjects throughout algebra. Hence the idea arises of a dual (...)
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  13. Models as Make-Believe.Adam Toon - 2010 - In Roman Frigg & Matthew Hunter (eds.), Beyond Mimesis and Convention: Representation in Art and Science. Boston Studies in Philosophy of Science.
    In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, (...)
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  14. The Tool Box of Science: Tools for the Building of Models with a Superconductivity Example.Nancy Cartwright, Towfic Shomar & Mauricio Suárez - 1995 - Poznan Studies in the Philosophy of the Sciences and the Humanities 44:137-149.
    We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction (...)
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  15. Models and Explanation.Alisa Bokulich - 2017 - In Lorenzo Magnani & Tommaso Wayne Bertolotti (eds.), Springer Handbook of Model-Based Science. Springer. pp. 103-118.
    Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...)
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  16.  93
    Modal Logic with Names.George Gargov & Valentin Goranko - 1993 - Journal of Philosophical Logic 22 (6):607 - 636.
    We investigate an enrichment of the propositional modal language L with a "universal" modality ■ having semantics x ⊧ ■φ iff ∀y(y ⊧ φ), and a countable set of "names" - a special kind of propositional variables ranging over singleton sets of worlds. The obtained language ℒ $_{c}$ proves to have a great expressive power. It is equivalent with respect to modal definability to another enrichment ℒ(⍯) of ℒ, where ⍯ is an additional modality with the semantics x ⊧ ⍯φ (...)
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  17. Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Lorenzo Magnani & Tommaso Wayne Bertolotti (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.
    The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use of (...)
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  18. Acceptance, Aggregation and Scoring Rules.Jake Chandler - 2013 - Erkenntnis 78 (1):201-217.
    As the ongoing literature on the paradoxes of the Lottery and the Preface reminds us, the nature of the relation between probability and rational acceptability remains far from settled. This article provides a novel perspective on the matter by exploiting a recently noted structural parallel with the problem of judgment aggregation. After offering a number of general desiderata on the relation between finite probability models and sets of accepted sentences in a Boolean sentential language, it is noted that (...)
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  19. On the Dangers of Making Scientific Models Ontologically Independent: Taking Richard Levins' Warnings Seriously.Rasmus Grønfeldt Winther - 2006 - Biology and Philosophy 21 (5):703-724.
    Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions (...)
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  20. The Value(s) of a Story: Theories, Models and Cognitive Values.Isabelle Peschard - 2007 - Principia 11 (2):151-169.
    This paper aims 1) to introduce the notion of theoretical story as a resource and source of constraint for the construction and assessment of models of phenomena; 2) to show the relevance of this notion for a better understanding of the role and nature of values in scientific activity. The reflection on the role of values and value judgments in scientific activity should be attentive, I will argue, to the distinction between models and the theoretical story that guides (...)
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  21. On Minimal Models for Pure Calculi of Names.Piotr Kulicki - 2013 - Logic and Logical Philosophy 22 (4):429–443.
    By pure calculus of names we mean a quantifier-free theory, based on the classical propositional calculus, which defines predicates known from Aristotle’s syllogistic and Leśniewski’s Ontology. For a large fragment of the theory decision procedures, defined by a combination of simple syntactic operations and models in two-membered domains, can be used. We compare the system which employs `ε’ as the only specific term with the system enriched with functors of Syllogistic. In the former, we do not need an empty (...)
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  22.  26
    Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting.Franck Varenne & Denis Phan - 2008 - In Nuno David, José Castro Caldas & Helder Coelho (eds.), Proceedings of the 3rd EPOS congress (Epistemological Perspectives On Simulations). Lisbon: pp. 51-69.
    Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, (...)
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  23.  84
    The Diversity of Models as a Means to Better Explanations in Economics.Emrah Aydinonat - forthcoming - Journal of Economic Methodology 25.
    In Economics Rules, Dani Rodrik (2015) argues that what makes economics powerful despite the limitations of each and every model is its diversity of models. Rodrik suggests that the diversity of models in economics improves its explanatory capacities, but he does not fully explain how. I offer a clearer picture of how models relate to explanations of particular economic facts or events, and suggest that the diversity of models is a means to better economic explanations.
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  24.  37
    Jamesian Finite Theism and the Problems of Suffering.Walter Scott Stepanenko - 2018 - European Journal for Philosophy of Religion 10 (4):1.
    William James advocated a form of finite theism, motivated by epistemological and moral concerns with scholastic theism and pantheism. In this article, I elaborate James’s case for finite theism and his strategy for dealing with these concerns, which I dub the problems of suffering. I contend that James is at the very least implicitly aware that the problem of suffering is not so much one generic problem but a family of related problems. I argue that one of James’s (...)
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  25. Experimentation on Analogue Models.Susan G. Sterrett - manuscript
    Summary Analogue models are actual physical setups used to model something else. They are especially useful when what we wish to investigate is difficult to observe or experiment upon due to size or distance in space or time: for example, if the thing we wish to investigate is too large, too far away, takes place on a time scale that is too long, does not yet exist or has ceased to exist. The range and variety of analogue models (...)
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  26.  32
    A Failed Encounter in Mathematics and Chemistry: The Folded Models of van ‘T Hoff and Sachse.Michael Friedman - 2016 - Teorie Vědy / Theory of Science 38 (3):359-386.
    Three-dimensional material models of molecules were used throughout the 19th century, either functioning as a mere representation or opening new epistemic horizons. In this paper, two case studies are examined: the 1875 models of van ‘t Hoff and the 1890 models of Sachse. What is unique in these two case studies is that both models were not only folded, but were also conceptualized mathematically. When viewed in light of the chemical research of that period not only (...)
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  27. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiæ 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of (...)
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  28.  16
    When Are Purely Predictive Models Best?Robert Northcott - unknown
    Can purely predictive models be useful in investigating causal systems? I argue ‘yes’. Moreover, in many cases not only are they useful, they are essential. The alternative is to stick to models or mechanisms drawn from well-understood theory. But a necessary condition for explanation is empirical success, and in many cases in social and field sciences such success can only be achieved by purely predictive models, not by ones drawn from theory. Alas, the attempt to use theory (...)
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  29.  85
    Intuition and Awareness of Abstract Models: A Challenge for Realists.Dimitris Kilakos - 2018 - Philosophies 3 (1):3-0.
    It is plausible to think that, in order to actively employ models in their inquiries, scientists should be aware of their existence. The question is especially puzzling for realists in the case of abstract models, since it is not obvious how this is possible. Interestingly, though, this question has drawn little attention in the relevant literature. Perhaps the most obvious choice for a realist is appealing to intuition. In this paper, I argue that if scientific models were (...)
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  30.  85
    Models as Signs: Extending Kralemann and Lattman’s Proposal on Modeling Models Within Peirce’s Theory of Signs.Sergio A. Gallegos - forthcoming - Synthese.
    In recent decades, philosophers of science have devoted considerable efforts to understand what models represent. One popular position is that models represent fictional situations. Another position states that, though models often involve fictional elements, they represent real objects or scenarios. Though these two positions may seem to be incompatible, I believe it is possible to reconcile them. Using a threefold distinction between different signs proposed by Peirce, I develop an argument based on a proposal recently made by (...)
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  31. Models at Work—Models in Decision Making.Ekaterina Svetlova & Vanessa Dirksen - 2014 - Science in Context 27 (4):561-577.
    In this topical section, we highlight the next step of research on modeling aiming to contribute to the emerging literature that radically refrains from approaching modeling as a scientific endeavor. Modeling surpasses “doing science” because it is frequently incorporated into decision-making processes in politics and management, i.e., areas which are not solely epistemically oriented. We do not refer to the production of models in academia for abstract or imaginary applications in practical fields, but instead highlight the real entwinement of (...)
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  32.  85
    Time in Cosmology.Chris Smeenk - 2013 - In A. Bardon & H. Dyke (eds.), The Blackwell Companion to the Philosophy of Time. Oxford: Blackwell. pp. 201-219.
    This essay aims to provide a self-contained introduction to time in relativistic cosmology that clarifies both how questions about the nature of time should be posed in this setting and the extent to which they have been or can be answered empirically. The first section below recounts the loss of Newtonian absolute time with the advent of special and general relativity, and the partial recovery of absolute time in the form of cosmic time in some cosmological models. Section II (...)
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  33.  89
    Labeled Calculi and Finite-Valued Logics.Matthias Baaz, Christian G. Fermüller, Gernot Salzer & Richard Zach - 1998 - Studia Logica 61 (1):7-33.
    A general class of labeled sequent calculi is investigated, and necessary and sufficient conditions are given for when such a calculus is sound and complete for a finite -valued logic if the labels are interpreted as sets of truth values. Furthermore, it is shown that any finite -valued logic can be given an axiomatization by such a labeled calculus using arbitrary "systems of signs," i.e., of sets of truth values, as labels. The number of labels needed is logarithmic (...)
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  34.  57
    Tiger Stripes and Embodied Systems: Hegel on Markets and Models.David Kolb - 2018 - In Michael J. Thompson (ed.), Hegel's Metaphysics and the Philosophy of Politics. New York, USA: Routledge. pp. 286-300.
    From Hegel's philosophy of nature, this essay develops a critique of economic models and market society, based on Hegel's notion of what it takes for a formally described system to be embodied and real.
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  35. Confirmation of Ecological and Evolutionary Models.Elisabeth A. Lloyd - 1987 - Biology and Philosophy 2 (3):277-293.
    In this paper I distinguish various ways in which empirical claims about evolutionary and ecological models can be supported by data. I describe three basic factors bearing on confirmation of empirical claims: fit of the model to data; independent testing of various aspects of the model, and variety of evident. A brief description of the kinds of confirmation is followed by examples of each kind, drawn from a range of evolutionary and ecological theories. I conclude that the greater complexity (...)
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  36.  35
    Computational Models (of Narrative) for Literary Studies.Antonio Lieto - 2015 - Semicerchio, Rivista di Poesia Comparata 2 (LIII):38-44.
    In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an important topic of investigation in (...)
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  37. Kinds of Models.Adam Morton & Mauricio Suárez - 2001 - In Model Validation: perspectives in hydrological science. pp. 11-22.
    We separate metaphysical from epistemic questions in the evaluation of models, taking into account the distinctive functions of models as opposed to theories. The examples a\are very varied.
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  38. Models and Truth.Uskali Mäki - 2010 - In M. Dorato M. Suàrez (ed.), Epsa Epistemology and Methodology of Science. Springer. pp. 177--187.
    In what follows, I will give examples of the sorts of step that can be taken towards spelling out the intuition that, after all, good models might be true. Along the way, I provide an outline of my account of models as ontologically and pragmatically constrained representations. And I emphasize the importance of examining models as functionally composed systems in which different components play different roles and only some components serve as relevant truth bearers. This disputes the (...)
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  39. Framework for Models and Simulations with Agents in Regard to Agent Simulations in Social Sciences: Emulation and Simulation.Franck Varenne - 2010 - In Alexandre Muzy, David R. C. Hill & Bernard P. Zeigler (eds.), Activity-Based Modeling and Simulation. Presses Universitaires Blaise-Pascal.
    The aim of this paper is to discuss the “Framework for M&S with Agents” (FMSA) proposed by Zeigler et al. [2000, 2009] in regard to the diverse epistemological aims of agent simulations in social sciences. We first show that there surely are great similitudes, hence that the aim to emulate a universal “automated modeler agent” opens new ways of interactions between these two domains of M&S with agents. E.g., it can be shown that the multi-level conception at the core of (...)
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  40. When Local Models Fail.Brian Epstein - 2008 - Philosophy of the Social Sciences 38 (1):3-24.
    Models treating the simple properties of social groups have a common shortcoming. Typically, they focus on the local properties of group members and the features of the world with which group members interact. I consider economic models of bureaucratic corruption, to show that (a) simple properties of groups are often constituted by the properties of the wider population, and (b) even sophisticated models are commonly inadequate to account for many simple social properties. Adequate models and social (...)
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  41. McKinsey Algebras and Topological Models of S4.1.Thomas Mormann - manuscript
    The aim of this paper is to show that every topological space gives rise to a wealth of topological models of the modal logic S4.1. The construction of these models is based on the fact that every space defines a Boolean closure algebra (to be called a McKinsey algebra) that neatly reflects the structure of the modal system S4.1. It is shown that the class of topological models based on McKinsey algebras contains a canonical model that can (...)
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  42.  51
    The Infinity From Nothing Paradox and the Immovable Object Meets the Irresistible Force.Nicholas Shackel - 2018 - European Journal for Philosophy of Science 8 (3):417-433.
    In this paper I present a novel supertask in a Newtonian universe that destroys and creates infinite masses and energies, showing thereby that we can have infinite indeterminism. Previous supertasks have managed only to destroy or create finite masses and energies, thereby giving cases of only finite indeterminism. In the Nothing from Infinity paradox we will see an infinitude of finite masses and an infinitude of energy disappear entirely, and do so despite the conservation of energy in (...)
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  43. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue (...)
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  44. There’s Plenty of Boole at the Bottom: A Reversible CA Against Information Entropy.Francesco Berto, Jacopo Tagliabue & Gabriele Rossi - 2016 - Minds and Machines 26 (4):341-357.
    “There’s Plenty of Room at the Bottom”, said the title of Richard Feynman’s 1959 seminal conference at the California Institute of Technology. Fifty years on, nanotechnologies have led computer scientists to pay close attention to the links between physical reality and information processing. Not all the physical requirements of optimal computation are captured by traditional models—one still largely missing is reversibility. The dynamic laws of physics are reversible at microphysical level, distinct initial states of a system leading to distinct (...)
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  45. Measuring Openness and Evaluating Digital Academic Publishing Models: Not Quite the Same Business.Giovanni De Grandis & Yrsa Neuman - 2014 - The Journal of Electronic Publishing 17 (3).
    In this article we raise a problem, and we offer two practical contributions to its solution. The problem is that academic communities interested in digital publishing do not have adequate tools to help them in choosing a publishing model that suits their needs. We believe that excessive focus on Open Access (OA) has obscured some important issues; moreover exclusive emphasis on increasing openness has contributed to an agenda and to policies that show clear practical shortcomings. We believe that academic communities (...)
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  46. What is the Value of Geometric Models to Understand Matter?Francoise Monnoyeur - 2015 - Epekeina 6 (2):1-13.
    This article analyzes the value of geometric models to understand matter with the examples of the Platonic model for the primary four elements (fire, air, water, and earth) and the models of carbon atomic structures in the new science of crystallography. How the geometry of these models is built in order to discover the properties of matter is explained: movement and stability for the primary elements, and hardness, softness and elasticity for the carbon atoms. These geometric (...) appear to have a double quality: firstly, they exhibit visually the scientific properties of matter, and secondly they give us the possibility to visualize its whole nature. Geometrical models appear to be the expression of the mind in the understanding of physical matter. (shrink)
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  47. Simple Tasks, Abstractions, and Semantic Dispositionalism.Adam C. Podlaskowski - 2012 - Dialectica 66 (4):453-470.
    According to certain kinds of semantic dispositionalism, what an agent means by her words is grounded by her dispositions to complete simple tasks. This sort of position is often thought to avoid the finitude problem raised by Kripke against simpler forms of dispositionalism. The traditional objection is that, since words possess indefinite (or infinite) extensions, and our dispositions to use words are only finite, those dispositions prove inadequate to serve as ground for what we mean by our words. I (...)
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  48. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. In this paper, I claim that mechanistic accounts of computation should allow for a broad variation of (...) of computation. In particular, some non-standard models should not be excluded a priori. The relationship between mathematical models of computation and mechanistically adequate models is studied in more detail. (shrink)
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  49. On Classical Finite Probability Theory as a Quantum Probability Calculus.David Ellerman - manuscript
    This paper shows how the classical finite probability theory (with equiprobable outcomes) can be reinterpreted and recast as the quantum probability calculus of a pedagogical or "toy" model of quantum mechanics over sets (QM/sets). There are two parts. The notion of an "event" is reinterpreted from being an epistemological state of indefiniteness to being an objective state of indefiniteness. And the mathematical framework of finite probability theory is recast as the quantum probability calculus for QM/sets. The point is (...)
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    Being There and Getting There: A View on the Nature and Application of Models.William M. Goodman - manuscript
    This paper updates (2017) a previously-presented* model of models, which can be used to clarify discussion and analysis in a variety of disputes and debates, since many such discussions hinge on displaying or implying models about how things are related. Knowing about models does not itself supply any new information about our world, but it might help us to recognize when and how information is being conveyed on these matters, or where possibly it is being obscured. If (...)
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