Software Simulation and Modeling in Psychology: MATLAB, SPSS, Excel and E-Prime describes all the stages of psychology experimentation, from the manipulation of factors, to statistical analysis, data modeling, and automated stimuli creation. The book shows how software can help automate various stages of the experiment for which operations may quickly become repetitive. For example, it shows how to compile data files (instead of opening files one by one to copy and paste), generate stimuli (instead of drawing one by one in a drawing software), and transform and recode tables of data. This type of modeling in psychology helps determine if a model fits the data, and also demonstrates that the algorithmic is not only useful, but essential for modeling data. Covers the entire process of experimenting, from designing an experiment, to modeling the data Shows how software can help automate various stages of the experiment for which operations may quickly become repetitive Contains sections on how to compile data files (instead of opening files one by one to copy and paste) and generate stimuli (instead of drawing one by one in a drawing software)
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.".
Thought experiments are a means of imaginative reasoning that lie at the heart of philosophy, from the pre-Socratics to the modern era, and they also play central roles in a range of fields, from physics to politics. The Routledge Companion to Thought Experiments is an invaluable guide and reference source to this multifaceted subject. Comprising over 30 chapters by a team of international contributors, the Companion covers the following important areas: · the history of thought experiments, from antiquity to the trolley problem and quantum non-locality; · thought experiments in the humanities, arts, and sciences, including ethics, physics, theology, biology, mathematics, economics, and politics; · theories about the nature of thought experiments; · new discussions concerning the impact of experimental philosophy, cross-cultural comparison studies, metaphilosophy, computer simulations, idealization, dialectics, cognitive science, the artistic nature of thought experiments, and metaphysical issues. This broad ranging Companion goes backwards through history and sideways across disciplines. It also engages with philosophical perspectives from empiricism, rationalism, naturalism, skepticism, pluralism, contextualism, and neo-Kantianism to phenomenology. This volume will be valuable for anyone studying the methods of philosophy or any discipline that employs thought experiments, as well as anyone interested in the power and limits of the mind.
This thoroughly, thoughtfully revised edition of a very successful textbook makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as to others interested in these models. Research since the publication of the first edition has been systematically incorporated into a framework of proven pedagogical value. Features of the second edition include: * A new section on spatiotemporal pattern processing * Coverage of ARTMAP networks (the supervised version of adaptive resonance networks) and recurrent back-propagation networks * A vastly expanded section on models of specific brain areas, such as the cerebellum, hippocampus, basal ganglia, and visual and motor cortex * Up-to-date coverage of applications of neural networks in areas such as combinatorial optimization and knowledge representation As in the first edition, the text includes extensive introductions to neuroscience and to differential and difference equations as appendices for students without the requisite background in these areas. As graphically revealed in the flowchart in the front of the book, the text begins with simpler processes and builds up to more complex multilevel functional systems. For more information visit the author's personal Web site at www.uta.edu/psychology/faculty/levine/
While laboratory research is the backbone of collecting experimental data in cognitive science, a rapidly increasing amount of research is now capitalizing on large-scale and real-world digital data. Each piece of data is a trace of human behavior and offers us a potential clue to understanding basic cognitive principles. However, we have to be able to put the pieces together in a reasonable way, which necessitates both advances in our theoretical models and development of new methodological techniques. The primary goal of this volume is to present cutting-edge examples of mining large-scale and naturalistic data to discover important principles of cognition and evaluate theories that would not be possible without such a scale. This book also has a mission to stimulate cognitive scientists to consider new ways to harness big data in order to enhance our understanding of fundamental cognitive processes. Finally, this book aims to warn of the potential pitfalls of using, or being over-reliant on, big data and to show how big data can work alongside traditional, rigorously gathered experimental data rather than simply supersede it. In sum, this groundbreaking volume presents cognitive scientists and those in related fields with an exciting, detailed, stimulating, and realistic introduction to big data – and to show how it may greatly advance our understanding of the principles of human memory, perception, categorization, decision-making, language, problem-solving, and representation.
Phil Johnson-Laird's theory of mental models has proved to be an influential development in the cognitive sciences. This theory aims to provide a detailed account of both reasoning and inference on the one hand, and language on the other. It can therefore be regarded as a step toward the much-sought-after unified theory of cognition.; This book provides an overview of mental models research. Some of the contributors were collaborators or former graduate students of Johnson-Laird, and between them they cover the main strands of mental models theory. After an appreciation of Johnson-Laird, the book covers topics including language Processing, Reasoning, Inference, The Role Of Emotions, And The Impact Of mental illnesses on thought processes.
This book presents an integrated framework for developing and testing computational models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models.
This book offers a unified theory of the major propertries of mind, including comprehension, inference, and consciousness. The author argues that we apprehend the world by building inner mental replicas of the relationships among objects and events that concern us. The mind is essentially a model-building device that can itself be modeled on a computer. The book provides a blueprint for building such a model and numberous important illustrations of how to do it.
This landmark text introduces the novice reader to what great thinkers think about thought. Unlike most texts, authors Jay Friedenberg and Gordon Silverman use a theoretical, rather than empirical, approach to examine the most important theories of mind from a variety of disciplinary perspectives. While experiments are discussed, they are used primarily to illustrate the specific characteristics of a model.
Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results.
An innovative, multifaceted approach to scientific experiments as designed by and shaped through interaction with the modeling process The role of scientific modeling in mediation between theories and phenomena is a critical topic within the philosophy of science, touching on issues from climate modeling to synthetic models in biology, high energy particle physics, and cognitive sciences. Offering a radically new conception of the role of data in the scientific modeling process as well as a new awareness of the problematic aspects of data, this cutting-edge volume offers a multifaceted view on experiments as designed and shaped in interaction with the modeling process. Contributors address such issues as the construction of models in conjunction with scientific experimentation; the status of measurement and the function of experiment in the identification of relevant parameters; how the phenomena under study are reconceived when accounted for by a model; and the interplay between experimenting, modeling, and simulation when results do not mesh. Highlighting the mediating role of models and the model-dependence (as well as theory-dependence) of data measurement, this volume proposes a normative and conceptual innovation in scientific modeling—that the phenomena to be investigated and modeled must not be precisely identified at the start but specified during the course of the interactions arising between experimental and modeling activities. Contributors: Nancy D. Cartwright, U of California, San Diego; Anthony Chemero, U of Cincinnati; Ronald N. Giere, U of Minnesota; Jenann Ismael, U of Arizona; Tarja Knuuttila, U of South Carolina; Andrea Loettgers, U of Bern, Switzerland; Deborah Mayo, Virginia Tech; Joseph Rouse, Wesleyan U; Paul Teller, U of California, Davis; Michael Weisberg, U of Pennsylvania; Eric Winsberg, U of South Florida.
Explains the phenomena, theoretical debates, experiments and historical development of experimental pragmatics, which investigates how utterances communicate a speaker's intended meaning.
|Author||: Ganesh R. Sinha,Jasjit S. Suri|
|Publisher||: Academic Press|
|Release Date||: 2020-03-17|
|ISBN 10||: 012819443X|
|Pages||: 396 pages|
Cognitive Informatics, Computer Modelling, and Cognitive Science: Theory, Case Studies, and Applications presents the theoretical background and history of cognitive science to help readers understand its foundations, philosophical and psychological aspects, and applications in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation, and information processing in the human brain are discussed, as is the theory of consciousness, neuroscience, intelligence, decision-making, mind and behavior analysis, and the various ways cognitive computing is used for information manipulation, processing and decision-making. Mathematical and computational models, structures and processes of the human brain are also covered, along with advances in machine learning, artificial intelligence, cognitive knowledge base, deep learning, cognitive image processing and suitable data analytics.
Handbook of Categorization in Cognitive Science, Second Edition presents the study of categories and the process of categorization as viewed through the lens of the founding disciplines of the cognitive sciences, and how the study of categorization has long been at the core of each of these disciplines. The literature on categorization reveals there is a plethora of definitions, theories, models and methods to apprehend this central object of study. The contributions in this handbook reflect this diversity. For example, the notion of category is not uniform across these contributions, and there are multiple definitions of the notion of concept. Furthermore, the study of category and categorization is approached differently within each discipline. For some authors, the categories themselves constitute the object of study, whereas for others, it is the process of categorization, and for others still, it is the technical manipulation of large chunks of information. Finally, yet another contrast has to do with the biological versus artificial nature of agents or categorizers. Defines notions of category and categorization Discusses the nature of categories: discrete, vague, or other Explores the modality effects on categories Bridges the category divide - calling attention to the bridges that have already been built, and avenues for further cross-fertilization between disciplines
Key Features --
An argument that computational models can shed light on referring, a fundamental and much-studied aspect of communication.
|Author||: Fred Adams,Osvaldo Pessoa Jr.,Joao E. Kogler Jr.|
|Publisher||: Vernon Press|
|Release Date||: 2019-04-18|
|ISBN 10||: 1622731115|
|Pages||: 324 pages|
This book consists of an edited collection of original essays of the highest academic quality by seasoned experts in their fields of cognitive science. The essays are interdisciplinary, drawing from many of the fields known collectively as “the cognitive sciences.” Topics discussed represent a significant cross-section of the most current and interesting issues in cognitive science. Specific topics include matters regarding machine learning and cognitive architecture, the nature of cognitive content, the relationship of information to cognition, the role of language and communication in cognition, the nature of embodied cognition, selective topics in visual cognition, brain connectivity, computation and simulation, social and technological issues within the cognitive sciences, and significant issues in the history of neuroscience. This book will be of interest to both professional researchers and newer students and graduate students in the fields of cognitive science—including computer science, linguistics, philosophy, psychology and neuroscience. The essays are in English and are designed to be as free as possible of technical jargon and therefore accessible to young scholars and to scholars who are new to the cognitive neurosciences. In addition to several entries by single authors, the book contains several interesting roundtables where researchers contribute answers to a central question presented to those in the focus group on one of the core areas listed above. This exciting approach provides a variety of perspectives from across disciplines on topics of current concern in the cognitive sciences.
|Author||: Stella Vosniadou,Daniel Kayser,Athanassios Protopapas|
|Publisher||: Taylor & Francis|
|Release Date||: 2017-09-29|
|ISBN 10||: 1317705564|
|Pages||: 976 pages|
This volume contains the invited lectures, invited symposia, symposia, papers and posters presented at the 2nd European Cognitive Science Conference held in Greece in May 2007. The papers presented in this volume range from empirical psychological studies and computational models to philosophical arguments, meta-analyses and even to neuroscientific experimentation. The quality of the work shows that the Cognitive Science Society in Europe is an exciting and vibrant one. There are 210 contributions by cognitive scientists from 27 different countries, including USA, France, UK, Germany, Greece, Italy, Belgium, Japan, Spain, the Netherlands, and Australia. This book will be of interest to anyone concerned with current research in Cognitive Science.
The Handbook of Cognitive Science provides an overview of recent developments in cognition research, relying upon non-classical approaches. Cognition is explained as the continuous interplay between brain, body, and environment, without relying on classical notions of computations and representation to explain cognition. The handbook serves as a valuable companion for readers interested in foundational aspects of cognitive science, and neuroscience and the philosophy of mind. The handbook begins with an introduction to embodied cognitive science, and then breaks up the chapters into separate sections on conceptual issues, formal approaches, embodiment in perception and action, embodiment from an artificial perspective, embodied meaning, and emotion and consciousness. Contributors to the book represent research overviews from around the globe including the US, UK, Spain, Germany, Switzerland, France, Sweden, and the Netherlands.
|Author||: Richard Alterman,David Kirsch|
|Publisher||: Psychology Press|
|Release Date||: 2013-12-16|
|ISBN 10||: 131775932X|
|Pages||: 160 pages|
This volume features the complete text of the material presented at the Twenty-Fifth Annual Conference of the Cognitive Science Society. As in previous years, the symposium included an interesting mixture of papers on many topics from researchers with diverse backgrounds and different goals, presenting a multifaceted view of cognitive science. This volume includes all papers, posters, and summaries of symposia presented at the leading conference that brings cognitive scientists together. The theme of this year's conference was the social, cultural, and contextual elements of cognition, including topics on collaboration, cultural learning, distributed cognition, and interaction.