Models And Inferences In Science
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Models And Inferences In Science
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Author : Emiliano Ippoliti
language : en
Publisher: Springer
Release Date : 2016-01-27
Models And Inferences In Science written by Emiliano Ippoliti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-27 with Science categories.
The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science.
Model Based Inference In The Life Sciences
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Author : David R. Anderson
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-22
Model Based Inference In The Life Sciences written by David R. Anderson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-22 with Science categories.
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Mental Models
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Author : Philip Nicholas Johnson-Laird
language : en
Publisher: Harvard University Press
Release Date : 1983
Mental Models written by Philip Nicholas Johnson-Laird and has been published by Harvard University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Psychology categories.
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.
Model Based Reasoning In Science And Technology
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Author : Ángel Nepomuceno-Fernández
language : en
Publisher: Springer Nature
Release Date : 2019-10-24
Model Based Reasoning In Science And Technology written by Ángel Nepomuceno-Fernández and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Philosophy categories.
This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning (MBR18), held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues concerning information visualization, experimental methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning.
Springer Handbook Of Model Based Science
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Author : Lorenzo Magnani
language : en
Publisher: Springer
Release Date : 2017-05-22
Springer Handbook Of Model Based Science written by Lorenzo Magnani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-22 with Technology & Engineering categories.
This handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in philosophy, the history of science, general epistemology, mathematics, cognitive and computer science, physics and life sciences, as well as engineering, architecture, and economics, this Handbook uses numerous diagrams, schemes and other visual representations to promote a better understanding of the concepts. This also makes it highly accessible to an audience of scholars and students with different scientific backgrounds. All in all, the Springer Handbook of Model-Based Science represents the definitive application-oriented reference guide to the interdisciplinary field of model-based reasoning.
Inference And Representation
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Author : Mauricio Suarez
language : en
Publisher: University of Chicago Press
Release Date : 2024
Inference And Representation written by Mauricio Suarez and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Inference categories.
"Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice. He begins by discussing the history and methodology of model building, helpfully charting the emergence of what he calls the modeling attitude, a nineteenth century and fin de siècle development. Throughout the book, prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book. After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents. He shows that scientists employ a plurality of different modeling relations in their representational practice - which also help them to assess the accuracy of their representations - while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez's inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation over the past several decades, as well as the consequences for epistemology of adopting an inferential conception of representation. His inferential conception is neutral between realism and instrumentalism, and he illustrates this by looking at, and briefly taking issue with, the epistemology of some of the most widely discussed philosophers in the literature"--
Model Based Reasoning In Science And Technology
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Author : Lorenzo Magnani
language : en
Publisher: Springer
Release Date : 2016-07-01
Model Based Reasoning In Science And Technology written by Lorenzo Magnani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-01 with Philosophy categories.
This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. It includes revised contributions presented during the international conference on Model-Based Reasoning (MBR’015), held on June 25-27 in Sestri Levante, Italy. The book is divided into three main parts, the first of which focuses on models, reasoning and representation. It highlights key theoretical concepts from an applied perspective, addressing issues concerning information visualization, experimental methods and design. The second part goes a step further, examining abduction, problem solving and reasoning. The respective contributions analyze different types of reasoning, discussing various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of historical, epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies in experimental research, this part aims at fostering new discussions and stimulating new ideas. All in all, the book provides researchers and graduate students in the field of applied philosophy, epistemology, cognitive science and artificial intelligence alike with an authoritative snapshot of current theories and applications of model-based reasoning.
Model Based Reasoning In Scientific Discovery
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Author : L. Magnani
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Model Based Reasoning In Scientific Discovery written by L. Magnani and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
The volume is based on the papers that were presented at the Interna tional Conference Model-Based Reasoning in Scientific Discovery (MBR'98), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 1998. The papers explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The study of diagnostic, visual, spatial, analogical, and temporal rea soning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of tradi tional notions of reasoning such as classical logic. Traditional accounts of scientific reasoning have restricted the notion of reasoning primarily to de ductive and inductive arguments. Understanding the contribution of model ing practices to discovery and conceptual change in science requires ex panding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philoso phy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model based reasoning to be considered in this book. The models are intended as in terpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.
Mental Models
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Author : Philip Nicholas Johnson-Laird
language : en
Publisher:
Release Date : 1983
Mental Models written by Philip Nicholas Johnson-Laird and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Cognitive science categories.
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.
Refining The Concept Of Scientific Inference When Working With Big Data
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2017-03-24
Refining The Concept Of Scientific Inference When Working With Big Data written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-24 with Mathematics categories.
The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.