Computational Models Of Learning
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Computational Models Of Brain And Behavior
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Author : Ahmed A. Moustafa
language : en
Publisher: John Wiley & Sons
Release Date : 2017-11-13
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 2017-11-13 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.
Production System Models Of Learning And Development
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Author : David Klahr
language : en
Publisher: MIT Press
Release Date : 1987
Production System Models Of Learning And Development written by David Klahr and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Psychology categories.
Cognitive psychologists have found the production systems class of computer simulation models to be one of the most direct ways to cast complex theories of human intelligence. There have been many scattered studies on production systems since they were first proposed as computational models of human problem-solving behavior by Allen Newell some twenty years ago, but this is the first book to focus exclusively on these important models of human cognition, collecting and giving many of the best examples of current research. In the first chapter, Robert Neches, Pat Langley, and David Klahr provide an overview of the fundamental issues involved in using production systems as a medium for theorizing about cognitive processes, emphasizing their theoretical power. The remaining chapters take up learning by doing and learning by understanding, discrimination learning, learning through incremental refinement, learning by chunking, procedural earning, and learning by composition. A model of cognitive development called BAIRN is described, and a final chapter reviews John Anderson's ACT theory and discusses how it can be used in intelligent tutoring systems, including one that teaches LISP programming skills. In addition to the editors, the contributors are Yuichiro Anzai (Hokkaido University, Japan), Paul Rosenbloom (Stanford) and Allen Newell (Carnegie-Mellon), Stellan Ohlsson (University of Pittsburgh), Clayton Lewis (University of Colorado, Boulder), Iain Wallace and Kevin Bluff (Deakon University, Australia), and John Anderson (Carnegie-Mellon). David Klahr is Professor and Head of the Department of Psychology at Carnegie-Mellon University. Pat Langley is Associate Professor, Department ofInformation and Computer Science, University of California, Irvine, and Robert Neches is Research Computer Scientist at University of Southern California Information Sciences Institute. "Production System Models of Learning and Development" is included in the series Computational Models of Cognition and Perception, edited by Jerome A. Feldman, Patrick J. Hayes, and David E.Rumelhart. A Bradford Book.
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.
The Cambridge Handbook Of Psycholinguistics
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Author : Michael Spivey
language : en
Publisher: Cambridge University Press
Release Date : 2012-08-20
The Cambridge Handbook Of Psycholinguistics written by Michael Spivey 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 2012-08-20 with Psychology categories.
Our ability to speak, write, understand speech and read is critical to our ability to function in today's society. As such, psycholinguistics, or the study of how humans learn and use language, is a central topic in cognitive science. This comprehensive handbook is a collection of chapters written not by practitioners in the field, who can summarize the work going on around them, but by trailblazers from a wide array of subfields, who have been shaping the field of psycholinguistics over the last decade. Some topics discussed include how children learn language, how average adults understand and produce language, how language is represented in the brain, how brain-damaged individuals perform in terms of their language abilities and computer-based models of language and meaning. This is required reading for advanced researchers, graduate students and upper-level undergraduates who are interested in the recent developments and the future of psycholinguistics.
Computational Models Of Reading
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Author : Erik D. Reichle
language : en
Publisher: Oxford University Press
Release Date : 2021
Computational Models Of Reading written by Erik D. Reichle 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 2021 with Computers categories.
Computational Models of Reading is a reference book that can be used to learn about reading research and how computer models have been used to explain and simulate the mental processes involved in reading. These mental processes include the identification of printed words, the active construction of larger units of meaning (for example, of sentences), and the integration of the latter into memory so that a text can be understood and remembered. The final chapter describes a new model of reading, in its entirety, and then reports simulations showing how it explains important findings related to reading.
Computational Modeling In Cognition
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Author : Stephan Lewandowsky
language : en
Publisher: SAGE Publications
Release Date : 2010-11-29
Computational Modeling In Cognition written by Stephan Lewandowsky and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-29 with Psychology categories.
Key Features --
Neural Networks Computational Models And Applications
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Author : Huajin Tang
language : en
Publisher: Springer
Release Date : 2010-11-22
Neural Networks Computational Models And Applications written by Huajin Tang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-22 with Computers categories.
Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.
An Introduction To Computational Learning Theory
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Author : Michael J. Kearns
language : en
Publisher: MIT Press
Release Date : 1994-08-15
An Introduction To Computational Learning Theory written by Michael J. Kearns and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-08-15 with Computers categories.
Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.
Computational Models For Cognitive Vision
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Author : Hiranmay Ghosh
language : en
Publisher: John Wiley & Sons
Release Date : 2020-08-18
Computational Models For Cognitive Vision written by Hiranmay Ghosh 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 2020-08-18 with Computers categories.
Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author’s ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as “artificial intelligence”. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: · knowledge representation techniques · evolution of cognitive architectures · deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.
Computational Models Of Scientific Discovery And Theory Formation
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Author : Jeff Shrager
language : en
Publisher: Morgan Kaufmann
Release Date : 1990
Computational Models Of Scientific Discovery And Theory Formation written by Jeff Shrager and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
This collection reports on recent advances in the study of scientific discovery and theory formation based on the computational techniques of artificial intelligence and cognitive science.