Author: Nick Chater
Publisher: OUP Oxford
ISBN: 0199216096
Category : Philosophy
Languages : en
Pages : 535
Book Description
The Probabilistic Mind is a follow-up to the influential and highly cited Rational Models of Cognition (OUP, 1998). It brings together developmetns in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
The Probabilistic Mind
Author: Nick Chater
Publisher: OUP Oxford
ISBN: 0199216096
Category : Philosophy
Languages : en
Pages : 535
Book Description
The Probabilistic Mind is a follow-up to the influential and highly cited Rational Models of Cognition (OUP, 1998). It brings together developmetns in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
Publisher: OUP Oxford
ISBN: 0199216096
Category : Philosophy
Languages : en
Pages : 535
Book Description
The Probabilistic Mind is a follow-up to the influential and highly cited Rational Models of Cognition (OUP, 1998). It brings together developmetns in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
Bayesian Rationality
Author: Mike Oaksford
Publisher: Oxford University Press
ISBN: 0198524498
Category : Philosophy
Languages : en
Pages : 342
Book Description
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.
Publisher: Oxford University Press
ISBN: 0198524498
Category : Philosophy
Languages : en
Pages : 342
Book Description
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.
Cognition and Chance
Author: Raymond S. Nickerson
Publisher: Psychology Press
ISBN: 113561461X
Category : Business & Economics
Languages : en
Pages : 798
Book Description
Lack of ability to think probabilistically makes one prone to a variety of irrational fears and vulnerable to scams designed to exploit probabilistic naiveté, impairs decision making under uncertainty, facilitates the misinterpretation of statistical information, and precludes critical evaluation of likelihood claims. Cognition and Chance presents an overview of the information needed to avoid such pitfalls and to assess and respond to probabilistic situations in a rational way. Dr. Nickerson investigates such questions as how good individuals are at thinking probabilistically and how consistent their reasoning under uncertainty is with principles of mathematical statistics and probability theory. He reviews evidence that has been produced in researchers' attempts to investigate these and similar types of questions. Seven conceptual chapters address such topics as probability, chance, randomness, coincidences, inverse probability, paradoxes, dilemmas, and statistics. The remaining five chapters focus on empirical studies of individuals' abilities and limitations as probabilistic thinkers. Topics include estimation and prediction, perception of covariation, choice under uncertainty, and people as intuitive probabilists. Cognition and Chance is intended to appeal to researchers and students in the areas of probability, statistics, psychology, business, economics, decision theory, and social dilemmas.
Publisher: Psychology Press
ISBN: 113561461X
Category : Business & Economics
Languages : en
Pages : 798
Book Description
Lack of ability to think probabilistically makes one prone to a variety of irrational fears and vulnerable to scams designed to exploit probabilistic naiveté, impairs decision making under uncertainty, facilitates the misinterpretation of statistical information, and precludes critical evaluation of likelihood claims. Cognition and Chance presents an overview of the information needed to avoid such pitfalls and to assess and respond to probabilistic situations in a rational way. Dr. Nickerson investigates such questions as how good individuals are at thinking probabilistically and how consistent their reasoning under uncertainty is with principles of mathematical statistics and probability theory. He reviews evidence that has been produced in researchers' attempts to investigate these and similar types of questions. Seven conceptual chapters address such topics as probability, chance, randomness, coincidences, inverse probability, paradoxes, dilemmas, and statistics. The remaining five chapters focus on empirical studies of individuals' abilities and limitations as probabilistic thinkers. Topics include estimation and prediction, perception of covariation, choice under uncertainty, and people as intuitive probabilists. Cognition and Chance is intended to appeal to researchers and students in the areas of probability, statistics, psychology, business, economics, decision theory, and social dilemmas.
The Intuitive Sources of Probabilistic Thinking in Children
Author: H. Fischbein
Publisher: Springer Science & Business Media
ISBN: 9027706263
Category : Psychology
Languages : en
Pages : 228
Book Description
About a year ago I promised my friend Fischbein a preface to his book of which I knew the French manuscript. Now with the printer's proofs under my eyes I like the book even better than I did then, because of, and influenced by, new experiences in the meantime, and fresh thoughts that crossed my mind. Have I been influenced by what I remembered from the manuscript? If so, it must have happened unconsciously. But of course, what struck me in this work a year ago, struck a responsive chord in my own mind. In the past, mathematics teaching theory has strongly been influenced by a view on mathematics as a heap of concepts, and on learning mathematics as concepts attainment. Mathematics teaching practice has been jeopardised by this theoretical approach, which in its most dangerous form expresses itself as a radical atomism. To concepts attainment Fischbein opposes acquisition of intuitions. In my own publications I avoided the word "intuition" because of the variety of its meanings across languages. For some time I have used the term "constitution of mathematical objects", which I think means the same as Fischbein's "acquisition of intuitions" - indeed as I view it, constituting a mental object precedes its conceptualising, and under this viewpoint I tried to observe mathematical activities of young children.
Publisher: Springer Science & Business Media
ISBN: 9027706263
Category : Psychology
Languages : en
Pages : 228
Book Description
About a year ago I promised my friend Fischbein a preface to his book of which I knew the French manuscript. Now with the printer's proofs under my eyes I like the book even better than I did then, because of, and influenced by, new experiences in the meantime, and fresh thoughts that crossed my mind. Have I been influenced by what I remembered from the manuscript? If so, it must have happened unconsciously. But of course, what struck me in this work a year ago, struck a responsive chord in my own mind. In the past, mathematics teaching theory has strongly been influenced by a view on mathematics as a heap of concepts, and on learning mathematics as concepts attainment. Mathematics teaching practice has been jeopardised by this theoretical approach, which in its most dangerous form expresses itself as a radical atomism. To concepts attainment Fischbein opposes acquisition of intuitions. In my own publications I avoided the word "intuition" because of the variety of its meanings across languages. For some time I have used the term "constitution of mathematical objects", which I think means the same as Fischbein's "acquisition of intuitions" - indeed as I view it, constituting a mental object precedes its conceptualising, and under this viewpoint I tried to observe mathematical activities of young children.
The Great Mental Models, Volume 1
Author: Shane Parrish
Publisher: Penguin
ISBN: 0593719972
Category : Business & Economics
Languages : en
Pages : 209
Book Description
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
Publisher: Penguin
ISBN: 0593719972
Category : Business & Economics
Languages : en
Pages : 209
Book Description
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
Probabilistic Knowledge
Author: Sarah Moss
Publisher: Oxford University Press
ISBN: 0198792158
Category : Mathematics
Languages : en
Pages : 281
Book Description
Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. She introduces the notion of probabilistic content and shows how it plays a central role not only in epistemology, but in the philosophy of mind and language. Just you can believe and assert propositions, you can believe and assert probabilistic contents.
Publisher: Oxford University Press
ISBN: 0198792158
Category : Mathematics
Languages : en
Pages : 281
Book Description
Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. She introduces the notion of probabilistic content and shows how it plays a central role not only in epistemology, but in the philosophy of mind and language. Just you can believe and assert propositions, you can believe and assert probabilistic contents.
Probabilistic Machine Learning
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Probability Theory
Author:
Publisher: Allied Publishers
ISBN: 9788177644517
Category :
Languages : en
Pages : 436
Book Description
Probability theory
Publisher: Allied Publishers
ISBN: 9788177644517
Category :
Languages : en
Pages : 436
Book Description
Probability theory
Music and Probability
Author: David Temperley
Publisher: MIT Press
ISBN: 0262201666
Category : Mathematics
Languages : en
Pages : 257
Book Description
Exploring the application of Bayesian probabilistic modeling techniques to musical issues, including the perception of key and meter.
Publisher: MIT Press
ISBN: 0262201666
Category : Mathematics
Languages : en
Pages : 257
Book Description
Exploring the application of Bayesian probabilistic modeling techniques to musical issues, including the perception of key and meter.
Probabilistic Thinking
Author: Egan J. Chernoff
Publisher: Springer Science & Business Media
ISBN: 940077155X
Category : Education
Languages : en
Pages : 746
Book Description
This volume provides a necessary, current and extensive analysis of probabilistic thinking from a number of mathematicians, mathematics educators, and psychologists. The work of 58 contributing authors, investigating probabilistic thinking across the globe, is encapsulated in 6 prefaces, 29 chapters and 6 commentaries. Ultimately, the four main perspectives presented in this volume (Mathematics and Philosophy, Psychology, Stochastics and Mathematics Education) are designed to represent probabilistic thinking in a greater context.
Publisher: Springer Science & Business Media
ISBN: 940077155X
Category : Education
Languages : en
Pages : 746
Book Description
This volume provides a necessary, current and extensive analysis of probabilistic thinking from a number of mathematicians, mathematics educators, and psychologists. The work of 58 contributing authors, investigating probabilistic thinking across the globe, is encapsulated in 6 prefaces, 29 chapters and 6 commentaries. Ultimately, the four main perspectives presented in this volume (Mathematics and Philosophy, Psychology, Stochastics and Mathematics Education) are designed to represent probabilistic thinking in a greater context.