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Dynamics of decision making: from evidence to preference and belief

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192700 Year: Pages: 259 DOI: 10.3389/978-2-88919-270-0 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology --- Psychology
Added to DOAB on : 2015-12-03 13:02:24
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At the core of the many debates throughout cognitive science concerning how decisions are made are the processes governing the time course of preference formation and decision. From perceptual choices, such as whether the signal on a radar screen indicates an enemy missile or a spot on a CT scan indicates a tumor, to cognitive value-based decisions, such as selecting an agreeable flatmate or deciding the guilt of a defendant, significant and everyday decisions are dynamic over time. Phenomena such as decoy effects, preference reversals and order effects are still puzzling researchers. For example, in a legal context, jurors receive discrete pieces of evidence in sequence, and must integrate these pieces together to reach a singular verdict. From a standard Bayesian viewpoint the order in which people receive the evidence should not influence their final decision, and yet order effects seem a robust empirical phenomena in many decision contexts. Current research on how decisions unfold, especially in a dynamic environment, is advancing our theoretical understanding of decision making. This Research Topic aims to review and further explore the time course of a decision - from how prior beliefs are formed to how those beliefs are used and updated over time, towards the formation of preferences and choices and post-decision processes and effects. Research literatures encompassing varied approaches to the time-scale of decisions will be brought into scope: a) Speeded decisions (and post-decision processes) that require the accumulation of noisy and possibly non-stationary perceptual evidence (e.g., randomly moving dots stimuli), within a few seconds, with or without temporal uncertainty. b) Temporally-extended, value-based decisions that integrate feedback values (e.g., gambling machines) and internally-generated decision criteria (e.g., when one switches attention, selectively, between the various aspects of several choice alternatives). c) Temporally extended, belief-based decisions that build on the integration of evidence, which interacts with the decision maker's belief system, towards the updating of the beliefs and the formation of judgments and preferences (as in the legal context). Research that emphasizes theoretical concerns (including optimality analysis) and mechanisms underlying the decision process, both neural and cognitive, is presented, as well as research that combines experimental and computational levels of analysis.

Classic Concepts in Anthropology

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ISBN: 9780990505082 Year: Language: English
Publisher: HAU Books Grant: Knowledge Unlatched - 101680
Subject: Anthropology
Added to DOAB on : 2018-07-10 11:01:02
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The late anthropologist Valerio Valeri (1944–98) was best known for his substantial writings on societies of Polynesia and eastern Indonesia. This volume, however, presents a lesser-known side of Valeri’s genius through a dazzlingly erudite set of comparative essays on core topics in the history of anthropological theory. Offering masterly discussions of anthropological thought about ritual, fetishism, cosmogonic myth, belief, caste, kingship, mourning, play, feasting, ceremony, and cultural relativism, Classic Concepts in Anthropology, presented here with a critical foreword by Rupert Stasch and Giovanni da Col, will be an eye-opening, essential resource for students and researchers not only in anthropology but throughout the humanities.

Improving Bayesian Reasoning: What Works and Why?

Authors: ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197453 Year: Pages: 207 DOI: 10.3389/978-2-88919-745-3 Language: English
Publisher: Frontiers Media SA
Subject: Psychology --- Science (General)
Added to DOAB on : 2016-04-07 11:22:02
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We confess that the first part of our title is somewhat of a misnomer. Bayesian reasoning is a normative approach to probabilistic belief revision and, as such, it is in need of no improvement. Rather, it is the typical individual whose reasoning and judgments often fall short of the Bayesian ideal who is the focus of improvement. What have we learnt from over a half-century of research and theory on this topic that could explain why people are often non-Bayesian? Can Bayesian reasoning be facilitated, and if so why? These are the questions that motivate this Frontiers in Psychology Research Topic. Bayes' theorem, named after English statistician, philosopher, and Presbyterian minister, Thomas Bayes, offers a method for updating one’s prior probability of an hypothesis H on the basis of new data D such that P(H|D) = P(D|H)P(H)/P(D). The first wave of psychological research, pioneered by Ward Edwards, revealed that people were overly conservative in updating their posterior probabilities (i.e., P(D|H)). A second wave, spearheaded by Daniel Kahneman and Amos Tversky, showed that people often ignored prior probabilities or base rates, where the priors had a frequentist interpretation, and hence were not Bayesians at all. In the 1990s, a third wave of research spurred by Leda Cosmides and John Tooby and by Gerd Gigerenzer and Ulrich Hoffrage showed that people can reason more like a Bayesian if only the information provided takes the form of (non-relativized) natural frequencies. Although Kahneman and Tversky had already noted the advantages of frequency representations, it was the third wave scholars who pushed the prescriptive agenda, arguing that there are feasible and effective methods for improving belief revision. Most scholars now agree that natural frequency representations do facilitate Bayesian reasoning. However, they do not agree on why this is so. The original third wave scholars favor an evolutionary account that posits human brain adaptation to natural frequency processing. But almost as soon as this view was proposed, other scholars challenged it, arguing that such evolutionary assumptions were not needed. The dominant opposing view has been that the benefit of natural frequencies is mainly due to the fact that such representations make the nested set relations perfectly transparent. Thus, people can more easily see what information they need to focus on and how to simply combine it. This Research Topic aims to take stock of where we are at present. Are we in a proto-fourth wave? If so, does it offer a synthesis of recent theoretical disagreements? The second part of the title orients the reader to the two main subtopics: what works and why? In terms of the first subtopic, we seek contributions that advance understanding of how to improve people’s abilities to revise their beliefs and to integrate probabilistic information effectively. The second subtopic centers on explaining why methods that improve non-Bayesian reasoning work as well as they do. In addressing that issue, we welcome both critical analyses of existing theories as well as fresh perspectives. For both subtopics, we welcome the full range of manuscript types.

Scepticism and belief in English witchcraft drama, 1538–1681

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ISBN: 9789198376876 Year: Pages: 360 Language: English
Publisher: Lund University Press
Subject: History --- Languages and Literatures
Added to DOAB on : 2019-03-21 11:21:02
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This book situates witchcraft drama within its cultural and intellectual context, highlighting the centrality of scepticism and belief in witchcraft to the genre. It is argued that these categories are most fruitfully understood not as static and mutually exclusive positions within the debate around witchcraft, but as rhetorical tools used within it. In drama, too, scepticism and belief are vital issues. The psychology of the witch character is characterised by a combination of impious scepticism towards God and credulous belief in the tricks of the witch’s master, the devil. Plays which present plausible depictions of witches typically use scepticism as a support: the witch’s power is subject to important limitations which make it easier to believe. Plays that take witchcraft less seriously present witches with unrestrained power, an excess of belief which ultimately induces scepticism. But scepticism towards witchcraft can become a veneer of rationality concealing other beliefs that pass without sceptical examination. The theatrical representation of witchcraft powerfully demonstrates its uncertain status as a historical and intellectual phenomenon; belief and scepticism in witchcraft drama are always found together, in creative tension with one another.

Delusions in Context

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ISBN: 9783319972022 9783319972015 Year: Pages: 130 DOI: 10.1007/978-3-319-97202-2 Language: English
Publisher: Springer Nature Grant: FP7 Ideas: European Research Council - 616358
Subject: Neurology --- Psychiatry
Added to DOAB on : 2019-01-15 13:34:06
License: Springer

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This open access book offers an exploration of delusions—unusual beliefs that can significantly disrupt people’s lives. Experts from a range of disciplinary backgrounds, including lived experience, clinical psychiatry, philosophy, clinical psychology, and cognitive neuroscience, discuss how delusions emerge, why it is so difficult to give them up, what their effects are, how they are managed, and what we can do to reduce the stigma associated with them. Taken as a whole, the book proposes that there is continuity between delusions and everyday beliefs. It is essential reading for researchers working on delusions and mental health more generally, and will also appeal to anybody who wants to gain a better understanding of what happens when the way we experience and interpret the world is different from that of the people around us.

Religion and Art: Rethinking Aesthetic and Auratic Experiences in 'Post-Secular' Times

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ISBN: 9783039210329 9783039210336 Year: Pages: 102 DOI: 10.3390/books978-3-03921-033-6 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Religion
Added to DOAB on : 2019-06-26 08:44:06
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How can we think of the “aura” of (sacred) contexts and (sacred) works? How to think of individual and collective (esthetic/religious) experiences? What to make of the manipulative dimension of (religious and esthetic) “auratic” experiences? Is the work of art still capable of mediating the experience of the “sacred,” and under what conditions? What is the significance of the “eschatological” dimension of both art and religion (the sense of “ending”)? Can theology offer a way to reaffirm the creative capacities of the human being as something that characterizes the very condition of being human? This Special Issue aspires to contribute to the growing literature on contemporary art and religion, and to explore the new ways of thinking of art and the sacred (in their esthetic, ideological, and institutional dimensions) in the context of contemporary culture.

Multi-Sensor Information Fusion

Authors: ---
ISBN: 9783039283026 9783039283033 Year: Pages: 602 DOI: 10.3390/books978-3-03928-303-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Keywords

linear regression --- covariance matrix --- data association --- sensor fusing --- SLAM --- multi-sensor data fusion --- conflicting evidence --- Dempster–Shafer evidence theory --- belief entropy --- similarity measure --- data classification --- fault diagnosis --- Bar-Shalom Campo --- Covariance Projection method --- data fusion --- distributed architecture --- Kalman filter --- linear constraints --- inconsistent data --- user experience evaluation --- user experience measurement --- eye-tracking --- facial expression --- galvanic skin response --- EEG --- interaction tracker --- self-reporting --- user experience platform --- mix-method approach --- image fusion --- multi-focus --- weight maps --- gradient domain --- fast guided filter. --- Dempster-Shafer evidence theory (DST) --- uncertainty measure --- open world --- closed world --- Deng entropy --- extended belief entropy --- sensor data fusion --- orthogonal redundant inertial measurement units --- data fusion architectures --- sensors bias --- fire source localization --- dynamic optimization --- global information --- the Range-Point-Range frame --- the Range-Range-Range frame --- sensor array --- SINS/DVL integrated navigation --- unscented information filter --- square root --- state probability approximation --- most suitable parameter form --- deep learning --- data preprocessing --- Human Activity Recognition (HAR) --- Internet of things (IoT) --- Industry 4.0 --- trajectory reconstruction --- low-cost sensors --- embedded systems --- powered two wheels (PTW) --- safe trajectory --- data fusion --- health management decision --- grey group decision-making --- health reliability degree --- maintenance decision --- sensor system --- least-squares filtering --- least-squares smoothing --- networked systems --- random parameter matrices --- random delays --- packet dropouts --- multi-sensor system --- multi-sensor information fusion --- particle swarm optimization --- sensor data fusion algorithm --- distributed intelligence system --- multi-sensor time series --- deep learning --- machine health monitoring --- time-distributed ConvLSTM model --- spatiotemporal feature learning --- optimal estimate --- unknown inputs --- distributed fusion --- augmented state Kalman filtering (ASKF) --- soft sensor --- coefficient of determination maximization strategy --- expectation maximization (EM) algorithm --- Gaussian mixture model (GMM) --- alumina concentration --- multi-sensor joint calibration --- high-dimensional fusion data (HFD) --- supervoxel --- Gaussian density peak clustering --- sematic segmentation --- multisensor data fusion --- multitarget tracking --- GMPHD --- sonar network --- RFS --- attitude estimation --- Kalman filter --- land vehicle --- magnetic angular rate and gravity (MARG) sensor --- quaternion --- yaw estimation --- network flow theory --- multitarget tracking --- spectral clustering --- A* search algorithm --- RTS smoother --- integer programming --- Surface measurement --- multi-sensor measurement --- surface modelling --- data fusion --- Gaussian process --- multi-sensor network --- observable degree analysis --- information fusion --- nonlinear system --- hybrid adaptive filtering --- weighted fusion estimation --- square-root cubature Kalman filter --- information filter --- surface quality control --- multi-sensor data fusion --- cutting forces --- vibration --- acoustic emission --- signal feature extraction methods --- predictive modeling techniques --- attitude --- orientation --- estimation --- Kalman filter --- quaternion --- manifold --- image registration --- evidential reasoning --- belief functions --- uncertainty --- DoS attack --- industrial cyber-physical system (ICPS) --- security zones --- mimicry security switch strategy --- fixed-point filter --- extended Kalman filter --- nested iterative method --- Steffensen’s iterative method --- convergence condition --- vehicular localization --- target positioning --- high-definition map --- vehicle-to-everything --- intelligent and connected vehicles --- intelligent transport system --- image registration --- non-rigid feature matching --- local structure descriptor --- Gaussian mixture model --- aircraft pilot --- workload --- multi-source data fusion --- fuzzy neural network --- principal component analysis --- parameter learning --- drift compensation --- domain adaption --- feature representations --- electronic nose --- data fusion --- dual gating --- MEMS accelerometer and gyroscope --- cardiac PET --- out-of-sequence --- multi-target tracking --- random finite set --- gaussian mixture probability hypothesis density --- multisensor system --- Gaussian process regression --- Bayesian reasoning method --- Dempster–Shafer evidence theory (DST) --- uncertainty measure --- novel belief entropy --- multi-sensor data fusion --- decision-level sensor fusion --- electronic nose --- subspace alignment --- interference suppression --- transfer --- evidence combination --- time-domain data fusion --- object classification --- uncertainty --- multirotor UAV --- precision landing --- artificial marker --- pose estimation --- sensor fusion --- camera --- LiDAR --- calibration --- plane matching --- ICP --- projection --- data fusion --- data registration --- adaptive distance function --- complex surface measurement --- Gaussian process model --- Dempster–Shafer evidence theory --- conflict measurement --- mutual support degree --- Hellinger distance --- Pignistic vector angle --- multi-sensor data fusion --- multi-environments --- state estimation --- unmanned aerial vehicle

Entropy Measures for Data Analysis: Theory, Algorithms and Applications

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ISBN: 9783039280322 9783039280339 Year: Pages: 260 DOI: 10.3390/books978-3-03928-033-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-01-07 09:21:22
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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Keywords

experiment of design --- empirical mode decomposition --- signal analysis --- similarity indices --- synchronization analysis --- auditory attention --- entropy measure --- linear discriminant analysis (LDA) --- support vector machine (SVM) --- auditory attention classifier --- electroencephalography (EEG) --- vague entropy --- distance induced vague entropy --- distance --- complex fuzzy set --- complex vague soft set --- entropy, entropy visualization --- entropy balance equation --- Shannon-type relations --- multivariate analysis --- machine learning evaluation --- data transformation --- sample entropy --- treadmill walking --- center of pressure displacement --- dual-tasking --- analog circuit --- fault diagnosis --- cross wavelet transform --- Tsallis entropy --- parametric t-distributed stochastic neighbor embedding --- support vector machine --- information transfer --- Chinese stock sectors --- effective transfer entropy --- market crash --- system coupling --- cross-visibility graphs --- image entropy --- geodesic distance --- Dempster-Shafer evidence theory --- uncertainty of basic probability assignment --- belief entropy --- plausibility transformation --- weighted Hartley entropy --- Shannon entropy --- learning --- information --- novelty detection --- non-probabilistic entropy --- learning systems --- permutation entropy --- embedded dimension --- short time records --- signal classification --- relevance analysis --- global optimization --- meta-heuristic --- firefly algorithm --- cross-entropy method --- co-evolution --- symbolic analysis --- ordinal patterns --- Permutation entropy --- conditional entropy of ordinal patterns --- Kolmogorov-Sinai entropy --- algorithmic complexity --- information entropy --- particle size distribution --- selfsimilar measure --- simulation --- data analysis --- entropy --- entropy measures --- automatic learning

Structural Prognostics and Health Management in Power & Energy Systems

Authors: --- --- --- --- et al.
ISBN: 9783039217663 9783039217670 Year: Pages: 218 DOI: 10.3390/books978-3-03921-767-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Philosophy
Added to DOAB on : 2020-01-30 16:39:46
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The idea of preparing an Energies Special Issue on “Structural Prognostics and Health Management in Power & Energy Systems” is to compile information on the recent advances in structural prognostics and health management (SPHM). Continued improvements on SPHM have been made possible through advanced signature analysis, performance degradation assessment, as well as accurate modeling of failure mechanisms by introducing advanced mathematical approaches/tools. Through combining deterministic and probabilistic modeling techniques, research on SPHM can provide assurance for new structures at a design stage and ensure construction integrity at a fabrication phase. Specifically, power and energy system failures occur under multiple sources of uncertainty/variability resulting from load variations in usage, material properties, geometry variations within tolerances, and other uncontrolled variations. Thus, advanced methods and applications for theoretical, numerical, and experimental contributions that address these issues on SPHM are desired and expected, which attempt to prevent overdesign and unnecessary inspection and provide tools to enable a balance between safety and economy to be achieved. This Special Issue has attracted submissions from China, USA, Portugal, and Italy. A total of 26 submissions were received and 11 articles finally published.

Keywords

prognostics --- residual useful life --- similarity-based approach --- supporting vector machine (SVM) --- reliability --- non-probabilistic reliability index --- sensitivity analysis --- techno-economic assessments --- life cycle cost --- vibration transmission mechanism --- underground powerhouse --- lateral-river vibration --- low frequency tail fluctuation --- rotation of hydraulic generator --- vertical axis wind turbine --- structural health monitoring --- operational modal analysis --- stochastic subspace identification --- vibration test --- offshore structures --- oil and gas platforms --- offshore wind turbines --- retrofitting activities --- renewable energy --- dynamic analysis --- wind and wave analysis --- dynamic analysis of the structure --- wave–structure interaction (WSI) --- probabilistic analyses of stochastic processes and frequency --- data-driven --- machine learning --- deep learning --- DNN --- prognostic and Health Management --- lithium-ion battery --- wind turbines --- health monitoring --- fault detection --- optimized deep belief networks --- supervisory control and data acquisition system --- multioperation condition --- wind turbine blade --- full-scale static test --- neural networks --- strain prediction --- dynamic fuzzy reliability analysis --- extremum surface response method --- weighted regression --- turbine blisk --- fuzzy safety criterion --- lithium-ion battery --- remaining useful life --- regeneration phenomenon --- wavelet decomposition --- NAR neural network --- empirical mode decomposition --- analysis mode decomposition --- analysis-empirical mode decomposition --- mode mixing --- sifting stop criterion

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