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A comprehensive introduction to the computational modeling of human cognition.
Book Synopsis Cognitive Modeling by : Thad A. Polk
Download or read book Cognitive Modeling written by Thad A. Polk and published by MIT Press. This book was released on 2002 with total page 1300 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to the computational modeling of human cognition.
Responding to an explosion of new mathematical and computational models used in the fields of cognitive science, this book provides simple tutorials concerning the development and testing of such models. The authors focus on a few key models, with a primary goal of equipping readers with the fundamental principles, methods, and tools necessary for evaluating and testing any type of model encountered in the field of cognitive science.
Book Synopsis Cognitive Modeling by : Jerome R. Busemeyer
Download or read book Cognitive Modeling written by Jerome R. Busemeyer and published by SAGE. This book was released on 2010 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Responding to an explosion of new mathematical and computational models used in the fields of cognitive science, this book provides simple tutorials concerning the development and testing of such models. The authors focus on a few key models, with a primary goal of equipping readers with the fundamental principles, methods, and tools necessary for evaluating and testing any type of model encountered in the field of cognitive science.
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.
Book Synopsis Introduction to Modeling Cognitive Processes by : Tom Verguts
Download or read book Introduction to Modeling Cognitive Processes written by Tom Verguts and published by MIT Press. This book was released on 2022-02-01 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
This work resulted from a workshop on the implications of the cognitive sciences for the philosophy of science held under the auspices of the Minnesota Center for Philosophy of Science. The workshop's theme was that the cognitive sciences - identified for the purposes of this project with three disciplinary clusters: artificial intelligence, cognitive psychology, and cognitive neuroscience - have reached sufficient maturity that they are now a valuable resource for philosophers of science who are developing general theories of science as a human activity. The emergence of cognitive science has by no means escaped the notice of philosophers or philosophers of science. Within the philosophy of science one can detect an emerging speciality, the philosophy of cognitive science, which would be parallel to such specialities as the philosophy of physics or the philosophy of biology. But the reverse is also happening. That is, the cognitive sciences are beginning to have a considerable impact on the content and methods of philosophy, particularly the philosophy of language and the philosophy of mind, but also on epistemology. The underlying hope is that the cognitive sciences might now come to play the sort of role within the philosophy of science that formal logic played for logical empiricism or that history of science played for the historical school. This development might permit the philosophy of science as a whole finally to move beyond the opposition between "logical" and "historical" approaches that has characterized the field since the 1960s. "Ronald N. Giere is Professor of Philosophy and Director of the Minnesota Center for Philosophy of Science at the University of Minnesota.".
Book Synopsis Cognitive Models of Science by : Ronald N. Giere
Download or read book Cognitive Models of Science written by Ronald N. Giere and published by U of Minnesota Press. This book was released on 1992 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work resulted from a workshop on the implications of the cognitive sciences for the philosophy of science held under the auspices of the Minnesota Center for Philosophy of Science. The workshop's theme was that the cognitive sciences - identified for the purposes of this project with three disciplinary clusters: artificial intelligence, cognitive psychology, and cognitive neuroscience - have reached sufficient maturity that they are now a valuable resource for philosophers of science who are developing general theories of science as a human activity. The emergence of cognitive science has by no means escaped the notice of philosophers or philosophers of science. Within the philosophy of science one can detect an emerging speciality, the philosophy of cognitive science, which would be parallel to such specialities as the philosophy of physics or the philosophy of biology. But the reverse is also happening. That is, the cognitive sciences are beginning to have a considerable impact on the content and methods of philosophy, particularly the philosophy of language and the philosophy of mind, but also on epistemology. The underlying hope is that the cognitive sciences might now come to play the sort of role within the philosophy of science that formal logic played for logical empiricism or that history of science played for the historical school. This development might permit the philosophy of science as a whole finally to move beyond the opposition between "logical" and "historical" approaches that has characterized the field since the 1960s. "Ronald N. Giere is Professor of Philosophy and Director of the Minnesota Center for Philosophy of Science at the University of Minnesota.".
A hilariously funny cookbook–cum–how–I–did–it memoir by the chef/restaurateur who created New York's dazzling Ápizz restaurant. At the age of thirty–seven, John LaFemina left a lucrative career as a jeweler to become a chef. Instead of going back to school, or getting on–the–job training, he did it the hard way: he bought the restaurant and then taught himself to cook. Today he owns two of New York's great Italian restaurants–Ápizz and Peasant–and is one of the city's most–talked–about chefs, earning rave reviews from fans and critics. In this gorgeous cookbook, he not only shares scores of recipes, but describes his life as a Canarsie boy learning about meatballs and macaroni in his mother's kitchen–and reveals how he drew on a lifetime of Italian cooking, and his own hard work and exquisite taste to create his dream restaurant from scratch. LaFemina takes us step–by–step through the process of finding the perfect location (and figuring out how many meatballs you have to sell to pay the rent), designing a restaurant, procuring all the necessary permits and licenses, and creating the menu. And this is just the first part of running a restaurant. He shares his experiences in dealing with the public and the press, unexpected disasters, and finally, basking in the glory of a popular restaurant. Along with his inspiring story, John LaFemina also shares 100 mouthwatering recipes, including: Lasagna with Braised Wild Boar Mushroom Risotto Veal, Beef, and Pork Meatballs with Ricotta Filling Open Ravioli with Roasted Butternut Squash Creamsicle Panna Cotta Chocolate Banana Bread Pudding
Book Synopsis Economic Theory and Cognitive Science by : Don Ross
Download or read book Economic Theory and Cognitive Science written by Don Ross and published by MIT Press. This book was released on 2005 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hilariously funny cookbook–cum–how–I–did–it memoir by the chef/restaurateur who created New York's dazzling Ápizz restaurant. At the age of thirty–seven, John LaFemina left a lucrative career as a jeweler to become a chef. Instead of going back to school, or getting on–the–job training, he did it the hard way: he bought the restaurant and then taught himself to cook. Today he owns two of New York's great Italian restaurants–Ápizz and Peasant–and is one of the city's most–talked–about chefs, earning rave reviews from fans and critics. In this gorgeous cookbook, he not only shares scores of recipes, but describes his life as a Canarsie boy learning about meatballs and macaroni in his mother's kitchen–and reveals how he drew on a lifetime of Italian cooking, and his own hard work and exquisite taste to create his dream restaurant from scratch. LaFemina takes us step–by–step through the process of finding the perfect location (and figuring out how many meatballs you have to sell to pay the rent), designing a restaurant, procuring all the necessary permits and licenses, and creating the menu. And this is just the first part of running a restaurant. He shares his experiences in dealing with the public and the press, unexpected disasters, and finally, basking in the glory of a popular restaurant. Along with his inspiring story, John LaFemina also shares 100 mouthwatering recipes, including: Lasagna with Braised Wild Boar Mushroom Risotto Veal, Beef, and Pork Meatballs with Ricotta Filling Open Ravioli with Roasted Butternut Squash Creamsicle Panna Cotta Chocolate Banana Bread Pudding
An introduction to the application of dynamical systems science to the cognitive sciences. Dynamical Cognitive Science makes available to the cognitive science community the analytical tools and techniques of dynamical systems science, adding the variables of change and time to the study of human cognition. The unifying theme is that human behavior is an "unfolding in time" whose study should be augmented by the application of time-sensitive tools from disciplines such as physics, mathematics, and economics, where change over time is of central importance. The book provides a fast-paced, comprehensive introduction to the application of dynamical systems science to the cognitive sciences. Topics include linear and nonlinear time series analysis, chaos theory, complexity theory, relaxation oscillators, and metatheoretical issues of modeling and theory building. Tools and techniques are discussed in the context of their application to basic cognitive science problems, including perception, memory, psychophysics, judgment and decision making, and consciousness. The final chapter summarizes the contemporary study of consciousness and suggests how dynamical approaches to cognitive science can help to advance our understanding of this central concept.
Book Synopsis Dynamical Cognitive Science by : Lawrence M. Ward
Download or read book Dynamical Cognitive Science written by Lawrence M. Ward and published by MIT Press. This book was released on 2002 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the application of dynamical systems science to the cognitive sciences. Dynamical Cognitive Science makes available to the cognitive science community the analytical tools and techniques of dynamical systems science, adding the variables of change and time to the study of human cognition. The unifying theme is that human behavior is an "unfolding in time" whose study should be augmented by the application of time-sensitive tools from disciplines such as physics, mathematics, and economics, where change over time is of central importance. The book provides a fast-paced, comprehensive introduction to the application of dynamical systems science to the cognitive sciences. Topics include linear and nonlinear time series analysis, chaos theory, complexity theory, relaxation oscillators, and metatheoretical issues of modeling and theory building. Tools and techniques are discussed in the context of their application to basic cognitive science problems, including perception, memory, psychophysics, judgment and decision making, and consciousness. The final chapter summarizes the contemporary study of consciousness and suggests how dynamical approaches to cognitive science can help to advance our understanding of this central concept.
The process of developing models, known as modeling, allows scientists to visualize difficult concepts, explain complex phenomena and clarify intricate theories. In recent years, science educators have greatly increased their use of modeling in teaching, especially real-time dynamic modeling, which is central to a scientific investigation. Modeling in science teaching is being used in an array of fields, everything from primary sciences to tertiary chemistry to college physics, and it is sure to play an increasing role in the future of education. Models and Modeling: Cognitive Tools for Scientific Enquiry is a comprehensive introduction to the use of models and modeling in science education. It identifies and describes many different modeling tools and presents recent applications of modeling as a cognitive tool for scientific enquiry.
Book Synopsis Models and Modeling by : Myint Swe Khine
Download or read book Models and Modeling written by Myint Swe Khine and published by Springer Science & Business Media. This book was released on 2011-03-01 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing models, known as modeling, allows scientists to visualize difficult concepts, explain complex phenomena and clarify intricate theories. In recent years, science educators have greatly increased their use of modeling in teaching, especially real-time dynamic modeling, which is central to a scientific investigation. Modeling in science teaching is being used in an array of fields, everything from primary sciences to tertiary chemistry to college physics, and it is sure to play an increasing role in the future of education. Models and Modeling: Cognitive Tools for Scientific Enquiry is a comprehensive introduction to the use of models and modeling in science education. It identifies and describes many different modeling tools and presents recent applications of modeling as a cognitive tool for scientific enquiry.
Thagard examines scientific development from the interdisciplinary perspective of cognitive science. Cognitive science combines insights from: philosophers analyze historical cases, psychologists carry out behavioral experiments, neuroscientists perform brain scans, and computer modelers write programs that simulate thought processes.
Book Synopsis The Cognitive Science of Science by : Paul Thagard
Download or read book The Cognitive Science of Science written by Paul Thagard and published by MIT Press (MA). This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thagard examines scientific development from the interdisciplinary perspective of cognitive science. Cognitive science combines insights from: philosophers analyze historical cases, psychologists carry out behavioral experiments, neuroscientists perform brain scans, and computer modelers write programs that simulate thought processes.
This book contains contributions presented during the international conference on Model-Based Reasoning (MBR ́012), held on June 21-23 in Sestri Levante, Italy. Interdisciplinary researchers discuss in this volume how scientific cognition and other kinds of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. Some of the contributions analyzed the problem of model-based reasoning in technology and stressed the issues of scientific and technological innovation. The book is divided in three main parts: models, mental models, representations; abduction, problem solving and practical reasoning; historical, epistemological and technological issues. The volume is based on the papers that were presented at the international
Book Synopsis Model-Based Reasoning in Science and Technology by : Lorenzo Magnani
Download or read book Model-Based Reasoning in Science and Technology written by Lorenzo Magnani and published by Springer Science & Business Media. This book was released on 2013-08-31 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains contributions presented during the international conference on Model-Based Reasoning (MBR ́012), held on June 21-23 in Sestri Levante, Italy. Interdisciplinary researchers discuss in this volume how scientific cognition and other kinds of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. Some of the contributions analyzed the problem of model-based reasoning in technology and stressed the issues of scientific and technological innovation. The book is divided in three main parts: models, mental models, representations; abduction, problem solving and practical reasoning; historical, epistemological and technological issues. The volume is based on the papers that were presented at the international
Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
Book Synopsis Encyclopedia of the Sciences of Learning by : Norbert M. Seel
Download or read book Encyclopedia of the Sciences of Learning written by Norbert M. Seel and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 3643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
