Results for 'prediction'

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  1. The Predictive Mind.Jakob Hohwy - 2013 - Oxford University Press UK.
    A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is (...)
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  2. Predictive Coding and Representationalism.Paweł Gładziejewski - 2016 - Synthese 193 (2).
    According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, (...)
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  3. Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
    Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks (...)
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  4.  5
    Can Predictive Processing Explain Self-Deception?Marko Jurjako - 2022 - Synthese 200 (4):1-20.
    The prediction error minimization framework denotes a family of views that aim at providing a unified theory of perception, cognition, and action. In this paper, I discuss some of the theoretical limitations of PEM. It appears that PEM cannot provide a satisfactory explanation of motivated reasoning, as instantiated in phenomena such as self-deception, because its cognitive ontology does not have a separate category for motivational states such as desires. However, it might be thought that this objection confuses levels of (...)
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  5. Predictive Processing, Perceiving and Imagining: Is to Perceive to Imagine, or Something Close to It?Michael D. Kirchhoff - 2018 - Philosophical Studies 175 (3):751-767.
    This paper examines the relationship between perceiving and imagining on the basis of predictive processing models in neuroscience. Contrary to the received view in philosophy of mind, which holds that perceiving and imagining are essentially distinct, these models depict perceiving and imagining as deeply unified and overlapping. It is argued that there are two mutually exclusive implications of taking perception and imagination to be fundamentally unified. The view defended is what I dub the ecological–enactive view given that it does not (...)
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  6. Prediction Versus Accommodation and the Risk of Overfitting.Christopher Hitchcock & Elliott Sober - 2004 - British Journal for the Philosophy of Science 55 (1):1-34.
    an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of (...)
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  7. Predictions and Primitive Ontology in Quantum Foundations: A Study of Examples.Valia Allori, Sheldon Goldstein, Roderich Tumulka & Nino Zanghì - 2014 - British Journal for the Philosophy of Science 65 (2):323-352.
    A major disagreement between different views about the foundations of quantum mechanics concerns whether for a theory to be intelligible as a fundamental physical theory it must involve a ‘primitive ontology’ (PO), i.e. variables describing the distribution of matter in four-dimensional space–time. In this article, we illustrate the value of having a PO. We do so by focusing on the role that the PO plays for extracting predictions from a given theory and discuss valid and invalid derivations of predictions. To (...)
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  8.  89
    Predictive Coding and Thought.Daniel Williams - 2020 - Synthese 197 (4):1749-1775.
    Predictive processing has recently been advanced as a global cognitive architecture for the brain. I argue that its commitments concerning the nature and format of cognitive representation are inadequate to account for two basic characteristics of conceptual thought: first, its generality—the fact that we can think and flexibly reason about phenomena at any level of spatial and temporal scale and abstraction; second, its rich compositionality—the specific way in which concepts productively combine to yield our thoughts. I consider two strategies for (...)
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  9. On Predicting.Fabrizio Cariani - forthcoming - Ergo: An Open Access Journal of Philosophy.
    I propose an account of the speech act of prediction that denies that the contents of prediction must be about the future and illuminates the relation between prediction and assertion. My account is a synthesis of two ideas: (i) that what is in the future in prediction is the time of discovery and (ii) that, as Benton and Turri recently argued, prediction is best characterized in terms of its constitutive norms.
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  10. Predicting Overall Car Performance Using Artificial Neural Network.Osama M. Al-Mubayyed, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (1):1-5.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.62 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...)
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  11. Prediction of Whether Mushroom is Edible or Poisonous Using Back-Propagation Neural Network.Eyad Sameh Alkronz, Khaled A. Moghayer, Mohamad Meimeh, Mohannad Gazzaz, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):1-8.
    Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the data. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether it is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JustNN software was used to training and validating the (...)
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  12. Iffy Predictions and Proper Expectations.Matthew A. Benton & John Turri - 2014 - Synthese 191 (8):1857-1866.
    What individuates the speech act of prediction? The standard view is that prediction is individuated by the fact that it is the unique speech act that requires future-directed content. We argue against this view and two successor views. We then lay out several other potential strategies for individuating prediction, including the sort of view we favor. We suggest that prediction is individuated normatively and has a special connection to the epistemic standards of expectation. In the process, (...)
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  13. Predictive Policing and the Ethics of Preemption.Daniel Susser - 2020 - In Ben Jones & Eduardo Mendieta (eds.), The Ethics of Policing: New Perspectives on Law Enforcement. New York: Nyu Press.
    The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and academics (...)
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  14. Predictive Processing and Perception: What Does Imagining Have to Do with It?Dan Cavedon-Taylor - forthcoming - Consciousness and Cognition.
    Predictive processing (PP) accounts of perception are unique not merely in that they postulate a unity between perception and imagination. Rather, they are unique in claiming that perception should be conceptualised in terms of imagination and that the two involve an identity of neural implementation. This paper argues against this postulated unity, on both conceptual and empirical grounds. Conceptually, the manner in which PP theorists link perception and imagination belies an impoverished account of imagery as cloistered from the external world (...)
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  15. Predictive Processing and the Representation Wars.Daniel Williams - 2018 - Minds and Machines 28 (1):141-172.
    Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the “representation wars” of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing’s account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based (...)
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  16.  48
    The Effect of Word Predictability on Reading Time is Logarithmic.Nathaniel J. Smith & Roger Levy - 2013 - Cognition 128 (3):302-319.
  17. Reward Prediction Error Signals Are Meta‐Representational.Nicholas Shea - 2014 - Noûs 48 (2):314-341.
    1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.
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  18. On Predicting Recidivism: Epistemic Risk, Tradeoffs, and Values in Machine Learning.Justin B. Biddle - forthcoming - Canadian Journal of Philosophy:1-21.
    Recent scholarship in philosophy of science and technology has shown that scientific and technological decision making are laden with values, including values of a social, political, and/or ethical character. This paper examines the role of value judgments in the design of machine-learning systems generally and in recidivism-prediction algorithms specifically. Drawing on work on inductive and epistemic risk, the paper argues that ML systems are value laden in ways similar to human decision making, because the development and design of ML (...)
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  19.  63
    Predictive Processing and the Representation Wars: A Victory for the Eliminativist.Adrian Downey - 2018 - Synthese 195 (12):5115-5139.
    In this paper I argue that, by combining eliminativist and fictionalist approaches toward the sub-personal representational posits of predictive processing, we arrive at an empirically robust and yet metaphysically innocuous cognitive scientific framework. I begin the paper by providing a non-representational account of the five key posits of predictive processing. Then, I motivate a fictionalist approach toward the remaining indispensable representational posits of predictive processing, and explain how representation can play an epistemologically indispensable role within predictive processing explanations without thereby (...)
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  20. Reintroducing Prediction to Explanation.Heather E. Douglas - 2009 - Philosophy of Science 76 (4):444-463.
    Although prediction has been largely absent from discussions of explanation for the past 40 years, theories of explanation can gain much from a reintroduction. I review the history that divorced prediction from explanation, examine the proliferation of models of explanation that followed, and argue that accounts of explanation have been impoverished by the neglect of prediction. Instead of a revival of the symmetry thesis, I suggest that explanation should be understood as a cognitive tool that assists us (...)
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  21.  9
    Predictive Processing and Extended Consciousness: Why the Machinery of Consciousness is (Probably) Still in the Head and the DEUTS Argument Won’T Let It Leak Outside.Marco Facchin & Niccolò Negro - unknown
    Consciousness vehicle externalism is the claim that the material machinery of a subject’s phenomenology partially leaks outside a subject’s brain, encompassing bodily and environmental structures. The DEUTS argument is the most prominent argument for CVE in the sensorimotor enactivists’ arsenal. In a recent series of publications, Kirchhoff and Kiverstein have deployed such an argument to claim that a prominent view of neural processing, namely predictive processing, is fully compatible with CVE. Indeed, in Kirchhoff and Kiverstein’s view, a proper understanding of (...)
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  22.  36
    Predicting the Past From Minimal Traces: Episodic Memory and its Distinction From Imagination and Preservation.Markus Werning - 2020 - Review of Philosophy and Psychology 11 (2):301-333.
    The paper develops an account of minimal traces devoid of representational content and exploits an analogy to a predictive processing framework of perception. As perception can be regarded as a prediction of the present on the basis of sparse sensory inputs without any representational content, episodic memory can be conceived of as a “prediction of the past” on the basis of a minimal trace, i.e., an informationally sparse, merely causal link to a previous experience. The resulting notion of (...)
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  23. ANN Model for Predicting Protein Localization Sites in Cells.Mohammed Nafez Abu Samra, Bilal Ezz El-Din Abed, Hossam Abdel Nasser Zaqout & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (9):43-50.
    To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and (...)
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  24.  6
    Predictions Without Futures.Sun-ha Hong - 2022 - History and Theory 61 (3):371-390.
  25. New Directions in Predictive Processing.Jakob Hohwy - 2020 - Mind and Language 35 (2):209-223.
    Predictive processing (PP) is now a prominent theoretical framework in the philosophy of mind and cognitive science. This review focuses on PP research with a relatively philosophical focus, taking stock of the framework and discussing new directions. The review contains an introduction that describes the full PP toolbox; an exploration of areas where PP has advanced understanding of perceptual and cognitive phenomena; a discussion of PP's impact on foundational issues in cognitive science; and a consideration of the philosophy of science (...)
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  26. Predicting Birth Weight Using Artificial Neural Network.Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (1):9-14.
    In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in hospitals. The evaluation (...)
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  27.  82
    Prediction, Accommodation, and the Logic of Discovery.Patrick Maher - 1988 - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:273 - 285.
    A widely endorsed thesis in the philosophy of science holds that if evidence for a hypothesis was not known when the hypothesis was proposed, then that evidence confirms the hypothesis more strongly than would otherwise be the case. The thesis has been thought to be inconsistent with Bayesian confirmation theory, but the arguments offered for that view are fallacious. This paper shows how the special value of prediction can in fact be given Bayesian explanation. The explanation involves consideration of (...)
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  28.  50
    Predictive Processing as a Systematic Basis for Identifying the Neural Correlates of Consciousness.Jakob Hohwy & Anil Seth - 2020 - Philosophy and the Mind Sciences 1 (II).
    The search for the neural correlates of consciousness is in need of a systematic, principled foundation that can endow putative neural correlates with greater predictive and explanatory value. Here, we propose the predictive processing framework for brain function as a promising candidate for providing this systematic foundation. The proposal is motivated by that framework’s ability to address three general challenges to identifying the neural correlates of consciousness, and to satisfy two constraints common to many theories of consciousness. Implementing the search (...)
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  29. Prediction with expert advice applied to the problem of prediction with expert advice.Daniel A. Herrmann - 2022 - Synthese 200 (4):1-24.
    We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in (...)
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  30. Prediction in Joint Action: What, When, and Where.Natalie Sebanz & Guenther Knoblich - 2009 - Topics in Cognitive Science 1 (2):353-367.
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  31. Predictive Coding Explains Binocular Rivalry: An Epistemological Review.Jakob Hohwy, Andreas Roepstorff & Karl Friston - 2008 - Cognition 108 (3):687-701.
  32.  38
    Prediction or Prophecy?: The Boundaries of Economic Foreknowledge and Their Socio-Political Consequences.Gregor Betz - 2006 - DUV.
    Gregor Betz explores the following questions: Where are the limits of economics, in particular the limits of economic foreknowledge? Are macroeconomic forecasts credible predictions or mere prophecies and what would this imply for the way economic policy decisions are taken? Is rational economic decision making possible without forecasting at all?
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  33.  85
    Predictive Brains, Dreaming Selves, Sleeping Bodies: How the Analysis of Dream Movement Can Inform a Theory of Self- and World-Simulation in Dreams.Jennifer M. Windt - 2018 - Synthese 195 (6):2577-2625.
    In this paper, I discuss the relationship between bodily experiences in dreams and the sleeping, physical body. I question the popular view that dreaming is a naturally and frequently occurring real-world example of cranial envatment. This view states that dreams are functionally disembodied states: in a majority of dreams, phenomenal experience, including the phenomenology of embodied selfhood, unfolds completely independently of external and peripheral stimuli and outward movement. I advance an alternative and more empirically plausible view of dreams as weakly (...)
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  34. Predictive Processing and the Phenomenology of Time Consciousness: A Hierarchical Extension of Rick Grush’s Trajectory Estimation Model.Wanja Wiese - 2017 - Philosophy and Predictive Processing.
    This chapter explores to what extent some core ideas of predictive processing can be applied to the phenomenology of time consciousness. The focus is on the experienced continuity of consciously perceived, temporally extended phenomena (such as enduring processes and successions of events). The main claim is that the hierarchy of representations posited by hierarchical predictive processing models can contribute to a deepened understanding of the continuity of consciousness. Computationally, such models show that sequences of events can be represented as states (...)
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  35. Neuroscientific Prediction and the Intrusion of Intuitive Metaphysics.David Rose, Wesley Buckwalter & Shaun Nichols - 2015 - Cognitive Science 39 (7).
    How might advanced neuroscience—in which perfect neuro-predictions are possible—interact with ordinary judgments of free will? We propose that peoples' intuitive ideas about indeterminist free will are both imported into and intrude into their representation of neuroscientific scenarios and present six experiments demonstrating intrusion and importing effects in the context of scenarios depicting perfect neuro-prediction. In light of our findings, we suggest that the intuitive commitment to indeterminist free will may be resilient in the face of scientific evidence against such (...)
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  36. Prediction and Explanation in Historical Natural Science.Carol E. Cleland - 2011 - British Journal for the Philosophy of Science 62 (3):551-582.
    In earlier work ( Cleland [2001] , [2002]), I sketched an account of the structure and justification of ‘prototypical’ historical natural science that distinguishes it from ‘classical’ experimental science. This article expands upon this work, focusing upon the close connection between explanation and justification in the historical natural sciences. I argue that confirmation and disconfirmation in these fields depends primarily upon the explanatory (versus predictive or retrodictive) success or failure of hypotheses vis-à-vis empirical evidence. The account of historical explanation that (...)
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  37.  96
    Prediction and the Periodic Table.Eric R. Scerri & John Worrall - 2001 - Studies in History and Philosophy of Science Part A 32 (3):407-452.
    The debate about the relative epistemic weights carried in favour of a theory by predictions of new phenomena as opposed to accommodations of already known phenomena has a long history. We readdress the issue through a detailed re-examination of a particular historical case that has often been discussed in connection with it—that of Mendeleev and the prediction by his periodic law of the three ‘new’ elements, gallium, scandium and germanium. We find little support for the standard story that these (...)
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  38.  40
    Predictive Processing and Anti-Representationalism.Marco Facchin - 2021 - Synthese 199 (3-4):11609-11642.
    Many philosophers claim that the neurocomputational framework of predictive processing entails a globally inferentialist and representationalist view of cognition. Here, I contend that this is not correct. I argue that, given the theoretical commitments these philosophers endorse, no structure within predictive processing systems can be rightfully identified as a representational vehicle. To do so, I first examine some of the theoretical commitments these philosophers share, and show that these commitments provide a set of necessary conditions the satisfaction of which allows (...)
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  39.  71
    Prediction and Accommodation Revisited.John Worrall - 2014 - Studies in History and Philosophy of Science Part A 45 (1):54-61.
    The paper presents a further articulation and defence of the view on prediction and accommodation that I have proposed earlier. It operates by analysing two accounts of the issue-by Patrick Maher and by Marc Lange-that, at least at first sight, appear to be rivals to my own. Maher claims that the time-order of theory and evidence may be important in terms of degree of confirmation, while that claim is explicitly denied in my account. I argue, however, that when his (...)
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  40. Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using (...)
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  41.  53
    Neuroscientific Prediction and the Intrusion of Intuitive Metaphysics.David Rose, Wesley Buckwalter & Shaun Nichols - 2017 - Cognitive Science 41 (2):482-502.
    How might advanced neuroscience—in which perfect neuro-predictions are possible—interact with ordinary judgments of free will? We propose that peoples' intuitive ideas about indeterminist free will are both imported into and intrude into their representation of neuroscientific scenarios and present six experiments demonstrating intrusion and importing effects in the context of scenarios depicting perfect neuro-prediction. In light of our findings, we suggest that the intuitive commitment to indeterminist free will may be resilient in the face of scientific evidence against such (...)
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  42.  25
    Minimizing prediction errors in predictive processing: from inconsistency to non-representationalism.Thomas van Es - 2020 - Phenomenology and the Cognitive Sciences 19 (5):997-1017.
    Predictive processing is an increasingly popular approach to cognition, perception and action. It says that the brain is essentially a hierarchical prediction machine. It is typically construed in a representationalist and inferentialist fashion so that the brain makes contentful inferences on the basis of representational models. In this paper, I argue that the predictive processing framework is inconsistent with this epistemic position. In particular, I argue that the combination of hierarchical modeling, contentful inferentialism and representationalism entail an internal inconsistency. (...)
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  43. Prediction Error Minimization, Mental and Developmental Disorder, and Statistical Theories of Consciousness.Jakob Hohwy - forthcoming - In Rocco Gennaro (ed.), Disturbed Consciousness: New Essays on Psychopathology and Theories of Consciousness. MIT Press.
    This chapter seeks to recover an approach to consciousness from a general theory of brain function, namely the prediction error minimization theory. The way this theory applies to mental and developmental disorder demonstrates its relevance to consciousness. The resulting view is discussed in relation to a contemporary theory of consciousness, namely the idea that conscious perception depends on Bayesian metacognition; this theory is also supported by considerations of psychopathology. This Bayesian theory is first disconnected from the higher-order thought theory, (...)
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  44. Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning.T. Yarkoni & J. Westfall - 2017 - Perspective on Psychological Science 12 (6):1100-1122.
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  45. Novel Predictions and the No Miracle Argument.Mario Alai - 2014 - Erkenntnis 79 (2):297-326.
    Predictivists use the no miracle argument to argue that “novel” predictions are decisive evidence for theories, while mere accommodation of “old” data cannot confirm to a significant degree. But deductivists claim that since confirmation is a logical theory-data relationship, predicted data cannot confirm more than merely deduced data, and cite historical cases in which known data confirmed theories quite strongly. On the other hand, the advantage of prediction over accommodation is needed by scientific realists to resist Laudan’s criticisms of (...)
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  46. Predicting Unethical Behavior: A Comparison of the Theory of Reasoned Action and the Theory of Planned Behavior. [REVIEW]Man Kit Chang - 1998 - Journal of Business Ethics 17 (16):1825-1834.
    This study is a comparison of the validity of theory of reasoned action and theory of planned behavior as applied to the area of moral behavior (i.e., illegal copying of software) using structural equation modeling. Data were collected from 181 university students on the various components of the theories and used to asses the influence of attitude, subjective norm, and perceived behavioral control on the intention to make unauthorized software copies. Theory of planned behavior was found to be better than (...)
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  47. Radical Predictive Processing.Andy Clark - 2015 - Southern Journal of Philosophy 53 (S1):3-27.
  48. Is Predictive Processing a Theory of Perceptual Consciousness?Tomas Marvan & Marek Havlík - 2021 - New Ideas in Psychology 61 (21).
    Predictive Processing theory, hotly debated in neuroscience, psychology and philosophy, promises to explain a number of perceptual and cognitive phenomena in a simple and elegant manner. In some of its versions, the theory is ambitiously advertised as a new theory of conscious perception. The task of this paper is to assess whether this claim is realistic. We will be arguing that the Predictive Processing theory cannot explain the transition from unconscious to conscious perception in its proprietary terms. The explanations offer (...)
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  49.  32
    Predictive Processes and the Peculiar Case of Music.Stefan Koelsch, Peter Vuust & Karl Friston - 2019 - Trends in Cognitive Sciences 23 (1):63-77.
  50. Predictive Perceptual Systems.Nico Orlandi - 2018 - Synthese 195 (6):2367-2386.
    This article attempts to clarify the commitments of a predictive coding approach to perception. After summarizing predictive coding theory, the article addresses two questions. Is a predictive coding perceptual system also a Bayesian system? Is it a Kantian system? The article shows that the answer to these questions is negative.
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