Switch to: References

Add citations

You must login to add citations.
  1. What is a Target System?Alkistis Elliott-Graves - 2020 - Biology and Philosophy 35 (2):1-22.
    Many phenomena in the natural world are complex, so scientists study them through simplified and idealised models. Philosophers of science have sought to explain how these models relate to the world. On most accounts, models do not represent the world directly, but through target systems. However, our knowledge of target systems is incomplete. First, what is the process by which target systems come about? Second, what types of entity are they? I argue that the basic conception of target systems, on (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • What is a Target System?Alkistis Elliott-Graves - 2020 - Biology and Philosophy 35 (2):1-22.
    Many phenomena in the natural world are complex, so scientists study them through simplified and idealised models. Philosophers of science have sought to explain how these models relate to the world. On most accounts, models do not represent the world directly, but through target systems. However, our knowledge of target systems is incomplete. First, what is the process by which target systems come about? Second, what types of entity are they? I argue that the basic conception of target systems, on (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • The Diversity of Rational Choice Theory: A Review Note.Catherine Herfeld - 2020 - Topoi 39 (2):329-347.
    In this paper, I review the literature on rational choice theory to scrutinize a number of criticisms that philosophers have voiced against its usefulness in economics. The paper has three goals: first, I argue that the debates about RCT have been characterized by disunity and confusion about the object under scrutiny, which calls into question the effectiveness of those criticisms. Second, I argue that RCT is not a single and unified choice theory—let alone an empirical theory of human behavior—as some (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark   1 citation  
  • Robustness Analysis and Tractability in Modeling.Chiara Lisciandra - 2017 - European Journal for Philosophy of Science 7 (1):79-95.
    In the philosophy of science and epistemology literature, robustness analysis has become an umbrella term that refers to a variety of strategies. One of the main purposes of this paper is to argue that different strategies rely on different criteria for justifications. More specifically, I will claim that: i) robustness analysis differs from de-idealization even though the two concepts have often been conflated in the literature; ii) the comparison of different model frameworks requires different justifications than the comparison of models (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Model Pluralism.Walter Veit - 2019 - Philosophy of the Social Sciences 50 (2):91-114.
    This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Getting Serious About Shared Features.Donal Khosrowi - 2020 - British Journal for the Philosophy of Science 71 (2):523-546.
    In Simulation and Similarity, Michael Weisberg offers a similarity-based account of the model–world relation, which is the relation in virtue of which successful models are successful. Weisberg’s main idea is that models are similar to targets in virtue of sharing features. An important concern about Weisberg’s account is that it remains silent on what it means for models and targets to share features, and consequently on how feature-sharing contributes to models’ epistemic success. I consider three potential ways of concretizing the (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • What is the Problem with Model-Based Explanation in Economics?Caterina Marchionni - 2017 - Disputatio 9 (47):603-630.
    The question of whether the idealized models of theoretical economics are explanatory has been the subject of intense philosophical debate. It is sometimes presupposed that either a model provides the actual explanation or it does not provide an explanation at all. Yet, two sets of issues are relevant to the evaluation of model-based explanation: what conditions should a model satisfy in order to count as explanatory and does the model satisfy those conditions. My aim in this paper is to unpack (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • The Explanation Paradox.Julian Reiss - 2012 - Journal of Economic Methodology 19 (1):43-62.
    This paper examines mathematical models in economics and observes that three mutually inconsistent hypotheses concerning models and explanation are widely held: (1) economic models are false; (2) economic models are nevertheless explanatory; and (3) only true accounts explain. Commentators have typically resolved the paradox by rejecting either one of these hypotheses. I will argue that none of the proposed resolutions work and conclude that therefore the paradox is genuine and likely to stay.
    Download  
     
    Export citation  
     
    Bookmark   40 citations  
  • Current Perspectives in Philosophy of Biology.Joaquin Suarez Ruiz & Rodrigo A. Lopez Orellana - 2019 - Humanities Journal of Valparaiso 14:7-426.
    Current Perspectives in Philosophy of Biology.
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  • An inferential and dynamic approach to modeling and understanding in biology.Rodrigo Lopez-Orellana, Juan Redmond & David Cortés-García - 2019 - Humanities Journal of Valparaiso 14:315-334.
    This paper aims to propose an inferential and dynamic approach to understanding with models in biology. Understanding plays a central role in the practice of modeling. From its links with the other two central elements of scientific research, experimentation, and explanation, we show its epistemic relevance to the case of explanation in biology. Furthermore, by including the notion of understanding, we propose a non-referentialist perspective on scientific models, which is determined by their use.
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  • The New Fiction View of Models.Fiora Salis - forthcoming - British Journal for the Philosophy of Science:axz015.
    How do models represent reality? There are two conditions that scientific models must satisfy to be representations of real systems, the aboutness condition and the epistemic condition. In this article, I critically assess the two main fictionalist theories of models as representations, the indirect fiction view and the direct fiction view, with respect to these conditions. And I develop a novel proposal, what I call ‘the new fiction view of models’. On this view, models are akin to fictional stories; they (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Homepage Eckhart Arnold.Eckhart Arnold (ed.) - 2001 - Munich: Preprint.
    Download  
     
    Export citation  
     
    Bookmark  
  • Why We Cannot Learn From Minimal Models.Roberto Fumagalli - 2016 - Erkenntnis 81 (3):433-455.
    Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to (...)
    Download  
     
    Export citation  
     
    Bookmark   8 citations  
  • In Search of Lost Deterrence – Two Essays on Deterrence and the Models Employed to Study the Phenomenon.Karl Sörenson - unknown
    To deter is central for strategic thinking. Some of the more astute observations regarding the dynamics of deterrence were made during the Cold War by game theorists. This set the stage for how deterrence has come to be studied. A strong methodological element like the research on deterrence’s reliance on game theory requires examination in order to understand what sort of knowledge it actually yields. What sort of knowledge does one acquire when deterrence is viewed through game theoretic models? How (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Representing in the Student Laboratory.Brandon Boesch - 2018 - Transversal: International Journal for the Historiography of Science 5:34-48.
    In this essay, I will expand the philosophical discussion about the representational practice in science to examine its role in science education through four case studies. The cases are of what I call ‘educational laboratory experiments’, performative models used representationally by students to come to a better understanding of theoretical knowledge of a scientific discipline. The studies help to demonstrate some idiosyncratic features of representational practices in science education, most importantly a lack of novelty and discovery built into the ELEs (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  • Idealizations and Understanding: Much Ado About Nothing?Emily Sullivan & Kareem Khalifa - 2019 - Australasian Journal of Philosophy 97 (4):673-689.
    Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealiza...
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Between Isolations and Constructions: Economic Models as Believable Worlds.Lukasz Hardt - 2016 - Poznan Studies in the Philosophy of the Sciences and the Humanities 106.
    As the title of this essay suggests, my concern is with the issue of what are economic models. However, the goal of the paper is not to offer an in-depth study on multiple approaches to modelling in economics, but rather to overcome the dichotomical divide between conceptualizing models as isolations and constructions. This is done by introducing the idea of economic models as believable worlds, precisely descriptions of mechanisms that refer to the essentials of the modelled targets. In doing so (...)
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  • I modelli in economia.Alessandra Basso & Caterina Marchionni - 2015 - Aphex 11.
    The paper reviews the philosophical literature on the epistemology of modelling in contemporary economics. In particular, it focuses on open questions concerning the epistemic role of models, the validity of inferences from the models to the world, and the legitimacy of their use for purposes of explanation, prediction and intervention.
    Download  
    Translate
     
     
    Export citation  
     
    Bookmark  
  • The Fiction View of Models Reloaded.Roman Frigg & James Nguyen - 2016 - The Monist 99 (3):225-242.
    In this paper we explore the constraints that our preferred account of scientific representation places on the ontology of scientific models. Pace the Direct Representation view associated with Arnon Levy and Adam Toon we argue that scientific models should be thought of as imagined systems, and clarify the relationship between imagination and representation.
    Download  
     
    Export citation  
     
    Bookmark   22 citations  
  • How Models Represent.James Nguyen - 2016 - Dissertation,
    Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Learning From Minimal Economic Models.Till Grüne-Yanoff - 2009 - Erkenntnis 70 (1):81-99.
    It is argued that one can learn from minimal economic models. Minimal models are models that are not similar to the real world, do not resemble some of its features, and do not adhere to accepted regularities. One learns from a model if constructing and analysing the model affects one’s confidence in hypotheses about the world. Economic models, I argue, are often assessed for their credibility. If a model is judged credible, it is considered to be a relevant possibility. Considering (...)
    Download  
     
    Export citation  
     
    Bookmark   55 citations  
  • Appraising Non-Representational Models.Till Grüne-Yanoff - unknown
    Many scientific models are non-representational in that they refer to merely possible processes, background conditions and results. The paper shows how such non-representational models can be appraised, beyond the weak role that they might play as heuristic tools. Using conceptual distinctions from the discussion of how-possibly explanations, six types of models are distinguished by their modal qualities of their background conditions, model processes and model results. For each of these types, an actual model example – drawn from economics, biology, psychology (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Derivational Robustness, Credible Substitute Systems and Mathematical Economic Models: The Case of Stability Analysis in Walrasian General Equilibrium Theory.D. Hands - 2016 - European Journal for Philosophy of Science 6 (1):31-53.
    This paper supports the literature which argues that derivational robustness can have epistemic import in highly idealized economic models. The defense is based on a particular example from mathematical economic theory, the dynamic Walrasian general equilibrium model. It is argued that derivational robustness first increased and later decreased the credibility of the Walrasian model. The example demonstrates that derivational robustness correctly describes the practices of a particular group of influential economic theorists and provides support for the arguments of philosophers who (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Non-Causal Understanding with Economic Models: The Case of General Equilibrium.Philippe Verreault-Julien - 2017 - Journal of Economic Methodology 24 (3):297-317.
    How can we use models to understand real phenomena if models misrepresent the very phenomena we seek to understand? Some accounts suggest that models may afford understanding by providing causal knowledge about phenomena via how-possibly explanations. However, general equilibrium models, for example, pose a challenge to this solution since their contribution appears to be purely mathematical results. Despite this, practitioners widely acknowledge that it improves our understanding of the world. I argue that the Arrow–Debreu model provides a mathematical how-possibly explanation (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  • How Could Models Possibly Provide How-Possibly Explanations?Philippe Verreault-Julien - 2019 - Studies in History and Philosophy of Science Part A 73:1-12.
    One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly and how-actually explanations. Whereas how-possibly (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Tools or Toys? On Specific Challenges for Modeling and the Epistemology of Models and Computer Simulations in the Social Sciences.Eckhart Arnold - manuscript
    Mathematical models are a well established tool in most natural sciences. Although models have been neglected by the philosophy of science for a long time, their epistemological status as a link between theory and reality is now fairly well understood. However, regarding the epistemological status of mathematical models in the social sciences, there still exists a considerable unclarity. In my paper I argue that this results from specific challenges that mathematical models and especially computer simulations face in the social sciences. (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Models in Science and Engineering: Imagining, Designing and Evaluating Representations.Michael Poznic - 2017 - Dissertation, Delft University of Technology
    The central question of this thesis is how one can learn about particular targets by using models of those targets. A widespread assumption is that models have to be representative models in order to foster knowledge about targets. Thus the thesis begins by examining the concept of representation from an epistemic point of view and supports an account of representation that does not distinguish between representation simpliciter and adequate representation. Representation, understood in the sense of a representative model, is regarded (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Isolation Is Not Characteristic of Models.Till Grüne-Yanoff - 2011 - International Studies in the Philosophy of Science 25 (2):119 - 137.
    Modelling cannot be characterized as isolating, nor models as isolations. This article presents three arguments to that effect, against Uskali Mäki's account of models. First, while isolation proceeds through a process of manipulation and control, modelling typically does not proceed through such a process. Rather, modellers postulate assumptions, without seeking to justify them by reference to a process of isolation. Second, while isolation identifies an isolation base?a concrete environment it seeks to control and manipulate?modelling typically does not identify such a (...)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  • De-Idealization by Commentary: The Case of Financial Valuation Models.Ekaterina Svetlova - 2013 - Synthese 190 (2):321-337.
    Is there a unique way to de-idealize models? If not, how might the possible ways of reducing the distortion between models and reality differ from each other? Based on an empirical case study conducted in financial markets, this paper discusses how a popular valuation model (the Discounted Cash Flow model) idealizes reality and how the market participants de-idealize it in concrete market situations. In contrast to Cartwright's view that economic models are generally over-constrained, this paper suggests that valuation models are (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • Credible Worlds, Capacities and Mechanisms.Robert Sugden - 2009 - Erkenntnis 70 (1):3-27.
    This paper asks how, in science in general and in economics in particular, theoretical models aid the understanding of real-world phenomena. Using specific models in economics and biology as test cases, it considers three alternative answers: that models are tools for isolating the ‘capacities’ of causal factors in the real world; that modelling is ‘conceptual exploration’ which ultimately contributes to the development of genuinely explanatory theories; and that models are credible counterfactual worlds from which inductive inferences can be made. The (...)
    Download  
     
    Export citation  
     
    Bookmark   55 citations  
  • Isolating Representations Versus Credible Constructions? Economic Modelling in Theory and Practice.Tarja Knuuttila - 2009 - Erkenntnis 70 (1):59-80.
    This paper examines two recent approaches to the nature and functioning of economic models: models as isolating representations and models as credible constructions. The isolationist view conceives of economic models as surrogate systems that isolate some of the causal mechanisms or tendencies of their respective target systems, while the constructionist approach treats them rather like pure constructions or fictional entities that nevertheless license different kinds of inferences. I will argue that whereas the isolationist view is still tied to the representationalist (...)
    Download  
     
    Export citation  
     
    Bookmark   29 citations  
  • 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 models provide understanding misguided? In (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • How Fictional Accounts Can Explain.Robert Sugden - 2013 - Journal of Economic Methodology 20 (3):237 - 243.
    In this note, I comment on Julian Reiss's paper ?The explanation paradox?. I argue in support of two of the propositions that make up that paradox (that economic models are false, and that they are explanatory) but challenge the third proposition, that only true accounts can explain. I defend the ?credible worlds? account of models as fictions that are explanatory by virtue of similarity relations with real-world phenomena. I argue that Reiss's objections to the role of subjective similarity judgements in (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  • Modelling and Representing: An Artefactual Approach to Model-Based Representation.Tarja Knuuttila - 2011 - Studies in History and Philosophy of Science Part A 42 (2):262-271.
    The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the (...)
    Download  
     
    Export citation  
     
    Bookmark   66 citations  
  • Incredible Worlds, Credible Results.Jaakko Kuorikoski & Aki Lehtinen - 2009 - Erkenntnis 70 (1):119-131.
    Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability (...)
    Download  
     
    Export citation  
     
    Bookmark   29 citations  
  • External Representations and Scientific Understanding.Jaakko Kuorikoski & Petri Ylikoski - 2015 - Synthese 192 (12):3817-3837.
    This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive explanations. Finally, (...)
    Download  
     
    Export citation  
     
    Bookmark   11 citations  
  • Resolving and Understanding Differences Between Agent-Based Accounts of Scientific Representation.Brandon Boesch - 2019 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 50 (2):195-213.
    Agent-based accounts of scientific representation all agree that the representational relationship is constituted by the actions of scientists. Despite this agreement, there are several differences in how agent-based accounts describe scientific representation. In this essay, I argue that these differences do not undercut the compatibility between the accounts. I make my argument by examining the nature of human agency and demonstrating that scientific, representational actions are multiply describable. I then argue that the differences between the accounts are valuable because they (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • The Market for Scientific Lemons, and the Marketization of Science.Jesús Zamora Bonilla - 2019 - Theoria : An International Journal for Theory, History and Fundations of Science 34 (1):133-145.
    Scientific research is based on the division of cognitive labour: every scientist has to trust that other colleagues have checked whether the items that are taken as knowledge, and she cannot check by herself, are reliable enough. I apply ideas from the field known as ‘information economics’ to analyse the scientists’ incentives to produce items of knowledge of an ‘adequate’ quality, under the assumption that a big part of what one observes in her empirical research is not available for the (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • What’s Wrong with Social Simulations?Eckhart Arnold - 2014 - The Monist 97 (3):359-377.
    This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. To examine this question, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling’s neighborhood segregation model and Axelrod’s reiterated Prisoner’s Dilemma simulations of the evolution of cooperation. It is argued that Schelling’s simulation is (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  • How to Use Fitness Landscape Models for the Analysis of Collective Decision-Making: A Case of Theory-Transfer and its Limitations.Peter Marks, Lasse Gerrits & Johannes Marx - 2019 - Biology and Philosophy 34 (1):7.
    There is considerable correspondence between theories and models used in biology and the social sciences. One type of model that is in use in both biology and the social sciences is the fitness landscape model. The properties of the fitness landscape model have been applied rather freely in the social domain. This is partly due to the versatility of the model, but it is also due to the difficulties of transferring a model to another domain. We will demonstrate that in (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • Fictional Models and Fictional Representations.Sim-Hui Tee - 2018 - Axiomathes 28 (4):375-394.
    Scientific models consist of fictitious elements and assumptions. Various attempts have been made to answer the question of how a model, which is sometimes viewed as a fiction, can explain or predict the target phenomenon adequately. I examine two accounts of models-as-fictions which are aiming at disentangling the myth of representing the reality by fictional models. I argue that both views have their own weaknesses in spite of many virtues. I propose to re-evaluate the problems of representation from a novel (...)
    Download  
     
    Export citation  
     
    Bookmark  
  • The Heuristic Defense of Scientific Models: An Incentive-Based Assessment.Armin W. Schulz - 2015 - Perspectives on Science 23 (4):424-442.
    It is undeniable that much scientific work is model-based. Despite this, the justification for this reliance on models is still controversial. A particular difficulty here is the fact that many scientific models are based on assumptions that do not describe the exact details of many or even any empirical situations very well. This raises the question of why it is that, despite their frequent lack of descriptive accuracy, employing models is scientifically useful.One..
    Download  
     
    Export citation  
     
    Bookmark  
  • Epistemic Contributions of Models: Conditions for Propositional Learning.François Claveau - 2015 - Perspectives on Science 23 (4):405-423.
    Models are powerful tools that can make us learn. Few contemporary observers of science doubt that, and economists agree; the highest honours of their discipline go to the most influential model builders. Among a long list of modellers who are Nobel laureates, we count Peter A. Diamond, Dale T. Mortensen and Christopher A. Pissarides, who were awarded the prize in 2010 as a recognition of their work in developing a model of the labor market—the DMP model.1While researchers agree that models (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
  • Model Templates Within and Between Disciplines: From Magnets to Gases – and Socio-Economic Systems.Tarja Knuuttila & Andrea Loettgers - 2016 - European Journal for Philosophy of Science 6 (3):377-400.
    One striking feature of the contemporary modelling practice is its interdisciplinary nature. The same equation forms, and mathematical and computational methods, are used across different disciplines, as well as within the same discipline. Are there, then, differences between intra- and interdisciplinary transfer, and can the comparison between the two provide more insight on the challenges of interdisciplinary theoretical work? We will study the development and various uses of the Ising model within physics, contrasting them to its applications to socio-economic systems. (...)
    Download  
     
    Export citation  
     
    Bookmark   5 citations  
  • Computational Functionalism for the Deep Learning Era.Ezequiel López-Rubio - 2018 - Minds and Machines 28 (4):667-688.
    Deep learning is a kind of machine learning which happens in a certain type of artificial neural networks called deep networks. Artificial deep networks, which exhibit many similarities with biological ones, have consistently shown human-like performance in many intelligent tasks. This poses the question whether this performance is caused by such similarities. After reviewing the structure and learning processes of artificial and biological neural networks, we outline two important reasons for the success of deep learning, namely the extraction of successively (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations