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Bayesian Cognitive Modeling


Bayesian Cognitive Modeling
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Bayesian Cognitive Modeling


Bayesian Cognitive Modeling
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Author : Michael D. Lee
language : en
Publisher: Cambridge University Press
Release Date : 2014-04-03

Bayesian Cognitive Modeling written by Michael D. Lee and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-03 with Psychology categories.


Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.



Bayesian Cognitive Modeling


Bayesian Cognitive Modeling
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Author : Michael D. Lee
language : en
Publisher: Cambridge University Press
Release Date : 2013

Bayesian Cognitive Modeling written by Michael D. Lee and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.


Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results.



Introduction To Modeling Cognitive Processes


Introduction To Modeling Cognitive Processes
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Author : Tom Verguts
language : en
Publisher: MIT Press
Release Date : 2022-02-01

Introduction To Modeling Cognitive Processes written by Tom Verguts and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-01 with Science categories.


An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and Bayesian models; and models of social interaction. All mathematical concepts are introduced gradually, with no background in advanced topics required. Hints and solutions for exercises and a glossary follow the main text. All code in the book is Python, with the Spyder editor in the Anaconda environment. A GitHub repository with Python files enables readers to access the computer code used and start programming themselves. The book is suitable as an introduction to modeling cognitive processes for students across a range of disciplines and as a reference for researchers interested in a broad overview.



Bayesian Rationality


Bayesian Rationality
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Author : Mike Oaksford
language : en
Publisher: Oxford University Press
Release Date : 2007-02-22

Bayesian Rationality written by Mike Oaksford and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-22 with Philosophy categories.


For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward.



Computational Models Of Brain And Behavior


Computational Models Of Brain And Behavior
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Author : Ahmed A. Moustafa
language : en
Publisher: John Wiley & Sons
Release Date : 2017-09-11

Computational Models Of Brain And Behavior written by Ahmed A. Moustafa and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-11 with Psychology categories.


A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndrome Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease Examines neural circuit models of serotonergic system (from microcircuits to cognition) Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.



An Introduction To Model Based Cognitive Neuroscience


An Introduction To Model Based Cognitive Neuroscience
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Author : Birte U. Forstmann
language : en
Publisher:
Release Date : 2015

An Introduction To Model Based Cognitive Neuroscience written by Birte U. Forstmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.


Two recent innovations, the emergence of formal cognitive models and the addition of cognitive neuroscience data to the traditional behavioral data, have resulted in the birth of a new, interdisciplinary field of study: model-based cognitive neuroscience. Despite the increasing scientific interest in model-based cognitive neuroscience, few active researchers and even fewer students have a good knowledge of the two constituent disciplines. The main goal of this edited collection is to promote the integration of cognitive modeling and cognitive neuroscience. Experts in the field will provide tutorial-style chapters that explain particular techniques and highlight their usefulness through concrete examples and numerous case studies. The book will also include a thorough list of references pointing the reader towards additional literature and online resources.



The Cambridge Handbook Of Computational Psychology


The Cambridge Handbook Of Computational Psychology
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Author : Ron Sun
language : en
Publisher: Cambridge University Press
Release Date : 2008-04-28

The Cambridge Handbook Of Computational Psychology written by Ron Sun and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-28 with Computers categories.


A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.



Computational Cognitive Modeling And Linguistic Theory


Computational Cognitive Modeling And Linguistic Theory
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Author : Adrian Brasoveanu
language : en
Publisher:
Release Date : 2020-10-09

Computational Cognitive Modeling And Linguistic Theory written by Adrian Brasoveanu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-09 with Language Arts & Disciplines categories.


This open access book introduces a general framework that allows natural language researchers to enhance existing competence theories with fully specified performance and processing components. Gradually developing increasingly complex and cognitively realistic competence-performance models, it provides running code for these models and shows how to fit them to real-time experimental data. This computational cognitive modeling approach opens up exciting new directions for research in formal semantics, and linguistics more generally, and offers new ways of (re)connecting semantics and the broader field of cognitive science. The approach of this book is novel in more ways than one. Assuming the mental architecture and procedural modalities of Anderson's ACT-R framework, it presents fine-grained computational models of human language processing tasks which make detailed quantitative predictions that can be checked against the results of self-paced reading and other psycho-linguistic experiments. All models are presented as computer programs that readers can run on their own computer and on inputs of their choice, thereby learning to design, program and run their own models. But even for readers who won't do all that, the book will show how such detailed, quantitatively predicting modeling of linguistic processes is possible. A methodological breakthrough and a must for anyone concerned about the future of linguistics! (Hans Kamp) This book constitutes a major step forward in linguistics and psycholinguistics. It constitutes a unique synthesis of several different research traditions: computational models of psycholinguistic processes, and formal models of semantics and discourse processing. The work also introduces a sophisticated python-based software environment for modeling linguistic processes. This book has the potential to revolutionize not only formal models of linguistics, but also models of language processing more generally. (Shravan Vasishth) This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.



Bayesian Modeling And Computation In Python


Bayesian Modeling And Computation In Python
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Author : Osvaldo A. Martin
language : en
Publisher: CRC Press
Release Date : 2021-12-28

Bayesian Modeling And Computation In Python written by Osvaldo A. Martin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-28 with Computers categories.


Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory. The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics. This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.