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Author: Wei Ji Ma Publisher: MIT Press ISBN: 0262047594 Category : Science Languages : en Pages : 409
Book Description
An accessible introduction to constructing and interpreting Bayesian models of perceptual decision-making and action. Many forms of perception and action can be mathematically modeled as probabilistic—or Bayesian—inference, a method used to draw conclusions from uncertain evidence. According to these models, the human mind behaves like a capable data scientist or crime scene investigator when dealing with noisy and ambiguous data. This textbook provides an approachable introduction to constructing and reasoning with probabilistic models of perceptual decision-making and action. Featuring extensive examples and illustrations, Bayesian Models of Perception and Action is the first textbook to teach this widely used computational framework to beginners. Introduces Bayesian models of perception and action, which are central to cognitive science and neuroscience Beginner-friendly pedagogy includes intuitive examples, daily life illustrations, and gradual progression of complex concepts Broad appeal for students across psychology, neuroscience, cognitive science, linguistics, and mathematics Written by leaders in the field of computational approaches to mind and brain
Author: Wei Ji Ma Publisher: MIT Press ISBN: 0262047594 Category : Science Languages : en Pages : 409
Book Description
An accessible introduction to constructing and interpreting Bayesian models of perceptual decision-making and action. Many forms of perception and action can be mathematically modeled as probabilistic—or Bayesian—inference, a method used to draw conclusions from uncertain evidence. According to these models, the human mind behaves like a capable data scientist or crime scene investigator when dealing with noisy and ambiguous data. This textbook provides an approachable introduction to constructing and reasoning with probabilistic models of perceptual decision-making and action. Featuring extensive examples and illustrations, Bayesian Models of Perception and Action is the first textbook to teach this widely used computational framework to beginners. Introduces Bayesian models of perception and action, which are central to cognitive science and neuroscience Beginner-friendly pedagogy includes intuitive examples, daily life illustrations, and gradual progression of complex concepts Broad appeal for students across psychology, neuroscience, cognitive science, linguistics, and mathematics Written by leaders in the field of computational approaches to mind and brain
Author: Richard A. Chechile Publisher: MIT Press ISBN: 0262044587 Category : Mathematics Languages : en Pages : 473
Book Description
An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis. This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book's premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics. The book first covers elementary probability theory, the binomial model, the multinomial model, and methods for comparing different experimental conditions or groups. It then turns its focus to distribution-free statistics that are based on having ranked data, examining data from experimental studies and rank-based correlative methods. Each chapter includes exercises that help readers achieve a more complete understanding of the material. The book devotes considerable attention not only to the linkage of statistics to practices in experimental science but also to the theoretical foundations of statistics. Frequentist statistical practices often violate their own theoretical premises. The beauty of Bayesian statistics, readers will learn, is that it is an internally coherent system of scientific inference that can be proved from probability theory.
Author: Andy Clark Publisher: Oxford University Press, USA ISBN: 0190217014 Category : Medical Languages : en Pages : 425
Book Description
This title brings together work on embodiment, action, and the predictive mind. At the core is the vision of human minds as prediction machines - devices that constantly try to stay one step ahead of the breaking waves of sensory stimulation, by actively predicting the incoming flow. In every situation we encounter, that complex prediction machinery is already buzzing, proactively trying to anticipate the sensory barrage. The book shows in detail how this strange but potent strategy of self-anticipation ushers perception, understanding, and imagination simultaneously onto the cognitive stage.
Author: Thomas Parr Publisher: MIT Press ISBN: 0262362287 Category : Science Languages : en Pages : 313
Book Description
The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.
Author: Julia Trommershauser Publisher: Oxford University Press ISBN: 019987476X Category : Psychology Languages : en Pages : 461
Book Description
This book is concerned with sensory cue integration both within and between sensory modalities, and focuses on the emerging way of thinking about cue combination in terms of uncertainty. These probabilistic approaches derive from the realization that our sensors are noisy and moreover are often affected by ambiguity. For example, mechanoreceptor outputs are variable and they cannot distinguish if a perceived force is caused by the weight of an object or by force we are producing ourselves. The probabilistic approaches elaborated in this book aim at formalizing the uncertainty of cues. They describe cue combination as the nervous system's attempt to minimize uncertainty in its estimates and to choose successful actions. Some computational approaches described in the chapters of this book are concerned with the application of such statistical ideas to real-world cue-combination problems. Others ask how uncertainty may be represented in the nervous system and used for cue combination. Importantly, across behavioral, electrophysiological and theoretical approaches, Bayesian statistics is emerging as a common language in which cue-combination problems can be expressed.
Author: Thomas Parr Publisher: MIT Press ISBN: 0262045354 Category : Science Languages : en Pages : 313
Book Description
The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.
Author: Mohan Matthen Publisher: OUP Oxford ISBN: 0191669040 Category : Philosophy Languages : en Pages : 944
Book Description
The Oxford Handbook of Philosophy of Perception is a survey by leading philosophical thinkers of contemporary issues and new thinking in philosophy of perception. It includes sections on the history of the subject, introductions to contemporary issues in the epistemology, ontology and aesthetics of perception, treatments of the individual sense modalities and of the things we perceive by means of them, and a consideration of how perceptual information is integrated and consolidated. New analytic tools and applications to other areas of philosophy are discussed in depth. Each of the forty-five entries is written by a leading expert, some collaborating with younger figures; each seeks to introduce the reader to a broad range of issues. All contain new ideas on the topics covered; together they demonstrate the vigour and innovative zeal of a young field. The book is accessible to anybody who has an intellectual interest in issues concerning perception.
Author: Kenji Doya Publisher: MIT Press ISBN: 026204238X Category : Bayesian statistical decision theory Languages : en Pages : 341
Book Description
Experimental and theoretical neuroscientists use Bayesian approaches to analyze the brain mechanisms of perception, decision-making, and motor control.
Author: Clark N. Glymour Publisher: MIT Press ISBN: 9780262072205 Category : Mathematics Languages : en Pages : 254
Book Description
This title provides an introduction to assumptions, algorithms, and techniques of causal Bayes nets and graphical causal models in the context of psychological examples. It demonstrates their potential as a powerful tool for guiding experimental inquiry.
Author: Gloria Cooper Publisher: TarcherPerigee ISBN: Category : Fiction Languages : en Pages : 88
Book Description
Featuring selections from The Lower case, the best-read page of the Columbia Journalism Review, Red Tape Holds Up New Bridge gives the Fourth Estate the once-over and comes up with non-stop fun.
Author: Wei Ji Ma
Author: Wei Ji Ma
Author: Richard A. Chechile
Author: Andy Clark
Author: Thomas Parr
Author: Julia Trommershauser
Author: Thomas Parr
Author: Mohan Matthen
Author: Kenji Doya
Author: Clark N. Glymour
Author: Gloria Cooper