Results for 'Prediction'

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  1. Causation, Prediction, and Search.Peter Spirtes, Clark Glymour, Scheines N. & Richard - 2000 - Mit Press: Cambridge.
  2. 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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  3.  27
    Surfing Uncertainty: Prediction, Action, and the Embodied Mind.Andy Clark - 2016 - Oxford University Press USA.
    How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...)
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  4.  4
    Serotonin, Predictive Processing and Psychedelics.Matteo Colombo - 2022 - Philosophy and the Mind Sciences 3.
    Letheby’s "Philosophy of Psychedelics" relies on Predictive Processing to try and find unifying explanations relevant to understanding how serotonergic psychedelics work in psychiatric therapy, what subjective experiences are associated with their use and whether such experiences are epistemically defective. But if Predictive Processing lacks genuinely explanatory unifying power, Letheby’s account of psychedelic therapy risks being unwarranted. In this commentary, I motivate this worry and sketch an alternative interpretation of psychedelic therapy within the Reinforcement Learning framework.
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  5.  11
    Extended Consciousness and Predictive Processing: A Third Wave View.Michael David Kirchhoff & Julian Kiverstein - 2019 - London, UK: Routledge.
    This book is forthcoming in Routledge. Here is the barest sketch of our aims: -/- We have two aims in this book. First, we aim to persuade you that conscious experience is sometimes realised by cycles of embodied and world-involving engagement. Second, we aim to persuade you that it is possible to develop and defend the thesis of extended consciousness through the increasingly powerful predictive processing theory developed in cognitive neuroscience.
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  6.  5
    Predictive Sentencing: Normative and Empirical Perspectives.Jan W. De Keijser, Julian V. Roberts & Jesper Ryberg (eds.) - 2019 - Hart Publishing.
    Predictive Sentencing addresses the role of risk assessment in contemporary sentencing practices. Predictive sentencing has become so deeply ingrained in Western criminal justice decision-making that despite early ethical discussions about selective incapacitation, it currently attracts little critique. Nor has it been subjected to a thorough normative and empirical scrutiny. This is problematic since much current policy and practice concerning risk predictions is inconsistent with mainstream theories of punishment. Moreover, predictive sentencing exacerbates discrimination and disparity in sentencing. Although structured risk assessments (...)
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  7. 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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  8. 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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  9.  37
    Predicting Children's Reading and Mathematics Achievement From Early Quantitative Knowledge and Domain-General Cognitive Abilities.Felicia W. Chu, Kristy vanMarle & David C. Geary - 2016 - Frontiers in Psychology 7.
  10. Busting Out: Predictive Brains, Embodied Minds, and the Puzzle of the Evidentiary Veil.Andy Clark - 2017 - Noûs 51 (4):727-753.
    Biological brains are increasingly cast as ‘prediction machines’: evolved organs whose core operating principle is to learn about the world by trying to predict their own patterns of sensory stimulation. This, some argue, should lead us to embrace a brain-bound ‘neurocentric’ vision of the mind. The mind, such views suggest, consists entirely in the skull-bound activity of the predictive brain. In this paper I reject the inference from predictive brains to skull-bound minds. Predictive brains, I hope to show, can (...)
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  11. 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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  12.  3
    Predictive Modeling of Individual Human Cognition: Upper Bounds and a New Perspective on Performance.Nicolas Riesterer, Daniel Brand & Marco Ragni - 2020 - Topics in Cognitive Science 12 (3):960-974.
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  13. 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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  14.  3
    Probability Designs: Literature and Predictive Processing.Karin Kukkonen - 2020 - Oup Usa.
    In Probability Designs, Karin Kukkonen presents the predictive processing model of cognition as a means of exploring narrative structure and reader experience. Utilizing the literary canon of various cultures, Kukkonen combines theory and cognitive science to analyze how reader expectation and prediction shape literature, and how literature accomplishes cognitive feats that determine the human capacity for free, exploratory thought.
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  15. 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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  16. 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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  17.  12
    The Predictive Dynamics of Happiness and Well-Being.Mark Miller, Erik Rietveld & Julian Kiverstein - 2021 - Sage Publications: Emotion Review 14 (1):15-30.
    Emotion Review, Volume 14, Issue 1, Page 15-30, January 2022. We offer an account of mental health and well-being using the predictive processing framework. According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence (...)
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  18.  84
    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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  19. 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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  20. 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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  21. 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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  22.  10
    The Predictive Dynamics of Happiness and Well-Being.Mark Miller, Julian Kiverstein & Erik Rietveld - 2021 - Emotion Review 14 (1):15-30.
    Emotion Review, Volume 14, Issue 1, Page 15-30, January 2022. We offer an account of mental health and well-being using the predictive processing framework. According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence (...)
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  23. Asymptotic Prediction for Future Observations of a Random Sample of Unknown Continuous Distribution.Magdy E. El-Adll, H. M. Barakat & Amany E. Aly - 2022 - Complexity 2022:1-15.
    When the first r lower extreme order statistics of a sample of large size n, 1 < r < s < n, are observed, asymptotic predictive intervals of the future extreme order statistic with a rank s are constructed. The only assumption that we adopt is that the first failure time is attracted to the Weibull distribution. In addition, we suggest an efficient point estimator of its shape parameter and then a confidence interval is constructed for it. Moreover, new interesting (...)
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    Predictive Brain Implants Are Unlikely to Decrease Patients' Autonomy.David Trafimow - 2015 - American Journal of Bioethics Neuroscience 6 (4):22-24.
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  25. 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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  26. 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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  27.  3
    Predicting Mathematics Achievement in Secondary Education: The Role of Cognitive, Motivational, and Emotional Variables.Amanda Abín, José Carlos Núñez, Celestino Rodríguez, Marisol Cueli, Trinidad García & Pedro Rosário - 2020 - Frontiers in Psychology 11.
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  28. On the Psychology of Prediction.Daniel Kahneman & Amos Tversky - 1973 - Psychological Review 80 (4):237-251.
    Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking (...)
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  29.  97
    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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  30.  59
    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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  31. 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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  32.  91
    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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  33. Predicting Verbal Learning and Memory Assessments of Older Adults Using Bayesian Hierarchical Models.Endris Assen Ebrahim & Mehmet Ali Cengiz - 2022 - Frontiers in Psychology 13.
    Verbal learning and memory summaries of older adults have usually been used to describe neuropsychiatric complaints. Bayesian hierarchical models are modern and appropriate approaches for predicting repeated measures data where information exchangeability is considered and a violation of the independence assumption in classical statistics. Such models are complex models for clustered data that account for distributions of hyper-parameters for fixed-term parameters in Bayesian computations. Repeated measures are inherently clustered and typically occur in clinical trials, education, cognitive psychology, and treatment follow-up. (...)
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  34. Predictive Processing in Sign Languages: A Systematic Review.Tomislav Radošević, Evie A. Malaia & Marina Milković - 2022 - Frontiers in Psychology 13.
    The objective of this article was to review existing research to assess the evidence for predictive processing in sign language, the conditions under which it occurs, and the effects of language mastery on the neural bases of PP. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. We searched peer-reviewed electronic databases and gray literature. We also searched the reference lists of records selected for the review and forward citations to identify all relevant publications. We searched (...)
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  35. 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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  36.  18
    Predicting Academic Dishonesty on National Examinations: The Roles of Gender, Previous Performance, Examination Center Change, City Change, and Region Change.Georgios D. Sideridis, Ioannis Tsaousis & Khaleel Al Harbi - 2016 - Ethics and Behavior 26 (3):215-237.
    The purpose of the present studies was to evaluate and predict academic cheating with regard to a national examination in a Middle East country. In Study 1, 4,024 students took part and potential cheaters were classified as those having discrepant scores in multiple administrations that exceeded 1 SD in absolute terms. A latent class mixture analysis suggested two pathways for potential cheating: The first path involved students—most male—who changed city or region of examination during test taking, and the second path (...)
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  37. Delusions: Between Phenomenology and Prediction. Introduction.Przemysław Nowakowski - 2014 - Avant: Trends in Interdisciplinary Studies 5 (3):11-16.
    One of the leading and central figures in research on delusions, Max Coltheart, presents and summarises his heretofore work in a short text. Miyazono and Bortolotti present an interesting argument aimed at the charges against the doxastic concept of delusions. Adams, Brown and Friston showcase a predictive-Bayesian concept of delusions. Young criticizes the current changes in the two-factor account of delusions and argues that the role of experience should not be dismissed within it. Kapusta presents an interesting, phenomenological approach to (...)
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  38. 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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  39.  30
    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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  40.  96
    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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  41. 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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  42. Predictive Processing and Body Representation.Stephen Gadsby & Jakob Hohwy - forthcoming - In Routledge Handbook of Bodily Awareness.
    We introduce the predictive processing account of body representation, according to which body representation emerges via a domain-general scheme of (long-term) prediction error minimisation. We contrast this account against one where body representation is underpinned by domain-specific systems, whose exclusive function is to track the body. We illustrate how the predictive processing account offers considerable advantages in explaining various empirical findings, and we draw out some implications for body representation research.
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  43.  81
    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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  44. 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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  45. Energy Efficiency Prediction Using Artificial Neural Network.Ahmed J. Khalil, Alaa M. Barhoom, Bassem S. Abu-Nasser, Musleh M. Musleh & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):1-7.
    Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...)
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  46. Predictive Coding Explains Binocular Rivalry: An Epistemological Review.Jakob Hohwy, Andreas Roepstorff & Karl Friston - 2008 - Cognition 108 (3):687-701.
  47. 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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  48. 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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  49.  9
    Differential Predictability of Four Dimensions of Affect Intensity.David C. Rubin, Rick H. Hoyle & Mark R. Leary - 2012 - Cognition and Emotion 26 (1):25-41.
  50. Prediction of Disorientation by Accelerometric and Gait Features in Young and Older Adults Navigating in a Virtually Enriched Environment.Stefan J. Teipel, Chimezie O. Amaefule, Stefan Lüdtke, Doreen Görß, Sofia Faraza, Sven Bruhn & Thomas Kirste - 2022 - Frontiers in Psychology 13.
    ObjectiveTo determine whether gait and accelerometric features can predict disorientation events in young and older adults.MethodsCognitively healthy younger and older participants navigated on a treadmill through a virtual representation of the city of Rostock featured within the Gait Real-Time Analysis Interactive Lab system. We conducted Bayesian Poisson regression to determine the association of navigation performance with domain-specific cognitive functions. We determined associations of gait and accelerometric features with disorientation events in real-time data using Bayesian generalized mixed effect models. The accuracy (...)
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