Springer Handbook of Model-Based Science
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 functio...
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2017
Springer Springer International Publishing AG Springer International Publishing |
| Edition: | 1 |
| Series: | Springer Handbooks |
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| ISBN: | 9783319305257, 3319305255 |
| ISSN: | 2522-8692, 2522-8706 |
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| Abstract | 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. |
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| AbstractList | 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. 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. |
| Author | Magnani, Lorenzo Bertolotti, Tommaso |
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| Copyright | 2017 Springer International Publishing Switzerland 2017 |
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| Editor | Magnani, Lorenzo Bertolotti, Tommaso |
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| Notes | Includes bibliographical references and index |
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| Snippet | This handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as... This handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning.It highlights the role of models as... |
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| SubjectTerms | Artificial Intelligence Cognitive Psychology Computational Intelligence Engineering General Engineering & Project Administration General References History and Philosophical Foundations of Physics Mathematical Logic and Foundations Model-based reasoning Philosophy of Science Qualitative reasoning Science Science -- Methodology |
| TableOfContents | Title Page
Preface
Table of Contents
Part I. Theoretical Issues in Models
1. The Ontology of Models
2. Models and Theories
3. Models and Representation
4. Models and Explanation
5. Models and Simulations
Part II. Theoretical and Cognitive Issues on Abduction and Scientific Inference
6. Reorienting the Logic of Abduction
7. Patterns of Abductive Inference
8. Forms of Abduction and an Inferential Taxonomy
9. Magnani's Manipulative Abduction
Part III. The Logic of Hypothetical Reasoning, Abduction, and Models
10. The Logic of Abduction: An Introduction
11. Qualitative Inductive Generalization and Confirmation
12. Modeling Hypothetical Reasoning by Formal Logics
13. Abductive Reasoning in Dynamic Epistemic Logic
14. Argumentation and Abduction in Dialogical Logic
15. Formal (In)Consistency, Abduction and Modalities
Part IV. Model-Based Reasoning in Science and the History of Science
16. Metaphor and Model-Based Reasoning in Mathematical Physics
17. Nancy Nersessian's Cognitive-Historical Approach
18. Physically Similar Systems - A History of the Concept
19. Hypothetical Models in Social Science
20. Model-Based Diagnosis
21. Thought Experiments in Model-Based Reasoning
Part V. Models in Mathematics
22. Diagrammatic Reasoning in Mathematics
23. Deduction, Diagrams and Model-Based Reasoning
24. Model-Based Reasoning in Mathematical Practice
25. Abduction and the Emergence of Necessary Mathematical Knowledge
Part VI. Model-Based Reasoning in Cognitive Science
26. Vision, Thinking, and Model-Based Inferences
27. Diagrammatic Reasoning
28. Embodied Mental Imagery in Cognitive Robots
29. Dynamical Models of Cognition
30. Complex versus Complicated Models of Cognition
31. From Neural Circuitry to Mechanistic Model-Based Reasoning
Part VII. Modelling and Computational Issues
32. Computational Aspects of Model-Based Reasoning
33. Computational Scientific Discovery
34. Computer Simulations and Computational Models in Science
35. Simulation of Complex Systems
36. Models and Experiments in Robotics
37. Biorobotics
Part VIII. Models in Physics, Chemistry and Life Sciences
38. Comparing Symmetries in Models and Simulations
39. Experimentation on Analogue Models
40. Models of Chemical Structure
41. Models in Geosciences
42. Models in the Biological Sciences
43. Models and Mechanisms in Cognitive Science
44. Model-Based Reasoning in the Social Sciences
Part IX. Models in Engineering, Architecture, and Economical and Human Sciences
45. Models in Architectural Design
46. Representational and Experimental Modeling in Archaeology
47. Models and Ideology in Design
48. Restructuring Incomplete Models in Innovators Marketplace on Data Jackets
49. Models in Pedagogy and Education
50. Model-Based Reasoning in Crime Prevention
51. Modeling in the Macroeconomics of Financial Markets
52. Application of Models from Social Science to Social Policy
53. Models and Moral Deliberation
About the Authors
Detailed Contents
Subject Index 27.4 Conclusions and Future Tasks 17.3 Hypothesis About the Creation of Scientific Concepts -- 17.4 Conclusions -- References -- 18 Physically Similar Systems - A History of the Concept -- 18.1 Similar Systems, the Twentieth Century Concept -- 18.2 Newton and Galileo -- 18.3 Late Nineteenth and Early Twentieth Century -- 18.4 1914: The Year of Physically Similar Systems -- 18.5 Physically Similar Systems: The Path in Retrospect -- References -- 19 Hypothetical Models in Social Science -- 19.1 Hypothetical Modeling as a Style of Reasoning -- 19.2 Models Versus Experiments: Representation, Isolation and Resemblance -- 19.3 Models and Simulations: Complexity, Tractability and Transparency -- 19.4 Epistemology of Models -- 19.5 Conclusions -- 19.A Appendix: J.H. von Thünen's Model of Agricultural Land Use in the Isolated State -- 19.B Appendix: T. Schelling's Agent-Based Model of Segregation in Metropolitan Areas -- References -- 20 Model-Based Diagnosis -- 20.1 A Basic Model for Diagnosis -- 20.2 A Review and Taxonomy of Knowledge Engineering Methods for Diagnosis -- 20.3 Model-Based Diagnostic Reasoning -- 20.4 A Motivation Example -- 20.5 Theory of Model-Based Diagnosis -- 20.6 Causal Graphs -- 20.7 Potential Conflict Structures -- 20.8 Example Revisited. A Complete Diagnostic Procedure -- 20.9 Refinement: Qualitative Diagnoses -- 20.10 Dynamic Systems Diagnosis: The Three-Tank Case -- 20.11 Incremental Diagnosis -- 20.12 Practical Example and Tools -- 20.13 Concluding Remarks -- References -- 21 Thought Experiments in Model-Based Reasoning -- 21.1 Overview -- 21.2 Historical Background -- 21.3 What Is a Thought Experiment? -- 21.4 What Is the Function of Thought Experiments? -- 21.5 How Do Thought Experiments Achieve Their Function? -- References -- Part E Models in Mathematics -- 22 Diagrammatic Reasoning in Mathematics -- 22.1 Diagrams as Cognitive Tools 7.1 General Characterization of Abductive Reasoning and Ibe -- 7.2 Three Dimensions for Classifying Patterns of Abduction -- 7.3 Factual Abduction -- 7.4 Law Abduction -- 7.5 Theoretical-Model Abduction -- 7.6 Second-Order Existential Abduction -- 7.7 Hypothetical (Common) Cause Abduction Continued -- 7.8 Further Applications of Abductive Inference -- References -- 8 Forms of Abduction and an Inferential Taxonomy -- 8.1 Abduction in the Overall Inferential Context -- 8.2 The Logicality of Abduction, Deduction, and Induction -- 8.3 Inverse Inferences -- 8.4 Discussion of Two Important Distinctions Between Types of Abduction -- 8.5 Conclusion -- References -- 9 Magnani's Manipulative Abduction -- 9.1 Magnani's Distinction Between Theoretical and Manipulative Abduction -- 9.2 Manipulative Abduction in Diagrammatic Reasoning -- 9.3 When Does Manipulative Abduction Take Place? -- 9.4 Manipulative Abduction as a Form of Practical Reasoning -- 9.5 The Ubiquity of Manipulative Abduction -- 9.6 Concluding Remarks -- References -- Part C The Logic of Hypothetical Reasoning, Abduction, and Models -- 10 The Logic of Abduction: An Introduction -- 10.1 Some History -- 10.2 Logical Abduction -- 10.3 Three Characterizations -- 10.4 Conclusions -- References -- 11 Qualitative Inductive Generalization and Confirmation -- 11.1 Adaptive Logics for Inductive Generalization -- 11.2 A First Logic for Inductive Generalization -- 11.3 More Adaptive Logics for Inductive Generalization -- 11.4 Qualitative Inductive Generalization and Confirmation -- 11.5 Conclusions -- 11.A Appendix: Blocking the Raven Paradox? -- References -- 12 Modeling Hypothetical Reasoning by Formal Logics -- 12.1 The Feasibility of the Project -- 12.2 Advantages and Drawbacks -- 12.3 Four Patterns of Hypothetical Reasoning -- 12.4 Abductive Reasoning and Adaptive Logics Intro -- Foreword: Thinking Inside and Outside -- Foreword -- Preface -- About the Editors -- About the Part Editors -- List of Authors -- Contents -- List of Abbreviations -- Part A Theoretical Issues in Models -- 1 The Ontology of Models -- 1.1 Kinds of Models: Examples from Scientific Practice -- 1.2 The Nature and Function of Models -- 1.3 Models as Analogies and Metaphors -- 1.4 Models Versus the Received View: Sentences and Structures -- 1.5 The Folk Ontology of Models -- 1.6 Models and Fiction -- 1.7 Mixed Ontologies: Models as Mediators and Epistemic Artifacts -- 1.8 Summary -- References -- 2 Models and Theories -- 2.1 The Received View of Scientific Theories -- 2.2 The Semantic View of Scientific Theories -- References -- 3 Models and Representation -- 3.1 Problems Concerning Model-Representation -- 3.2 General Griceanism and Stipulative Fiat -- 3.3 The Similarity Conception -- 3.4 The Structuralist Conception -- 3.5 The Inferential Conception -- 3.6 The Fiction View of Models -- 3.7 Representation-as -- 3.8 Envoi -- References -- 4 Models and Explanation -- 4.1 The Explanatory Function of Models -- 4.2 Explanatory Fictions: Can Falsehoods Explain? -- 4.3 Explanatory Models and Noncausal Explanations -- 4.4 How-Possibly versus How-Actually Model Explanations -- 4.5 Tradeoffs in Modeling: Explanation versus Other Functions for Models -- 4.6 Conclusion -- References -- 5 Models and Simulations -- 5.1 Theory-Based Simulation -- 5.2 Simulation not Driven by Theory -- 5.3 What is Philosophically Novel About Simulation? -- 5.4 Computational Simulation and Human Cognition -- References -- Part B Theoretical and Cognitive Issues on Abduction and Scientific Inference -- 6 Reorienting the Logic of Abduction -- 6.1 Abduction -- 6.2 Knowledge -- 6.3 Logic -- References -- 7 Patterns of Abductive Inference 12.5 The Problem of Multiple Explanatory Hypotheses -- 12.6 The Standard Format of Adaptive Logics -- 12.7 LAr_s: A Logic for Practical Singular Fact Abduction -- 12.8 MLA_ss: A Logic for Theoretical Singular Fact Abduction -- 12.9 Conclusions -- 12.A Appendix: Formal Presentations of the Logics LAr_s and MLA_ss -- References -- 13 Abductive Reasoning in Dynamic Epistemic Logic -- 13.1 Classical Abduction -- 13.2 A Dynamic Epistemic Perspective -- 13.3 Representing Knowledge and Beliefs -- 13.4 Abductive Problem and Solution -- 13.5 Selecting the Best Explanation -- 13.6 Integrating the Best Solution -- 13.7 Working with the Explanations -- 13.8 A Brief Exploration to Nonideal Agents -- 13.9 Conclusions -- References -- 14 Argumentation and Abduction in Dialogical Logic -- 14.1 Reasoning as a Human Activity -- 14.2 Logic and Argumentation: The Divorce -- 14.3 Logic and Argumentation: A Reconciliation -- 14.4 Beyond Deductive Inference: Abduction -- 14.5 Abduction in Dialogical Logic -- 14.6 Hypothesis: What Kind of Speech Act? -- 14.7 Conclusions -- References -- 15 Formal (In)consistency, Abduction and Modalities -- 15.1 Paraconsistency -- 15.2 Logics of Formal Inconsistency -- 15.3 Abduction -- 15.4 Modality -- 15.5 On Alternative Semantics for mbC -- 15.6 Conclusions -- References -- Part D Model-Based Reasoning in Science and the History of Science -- 16 Metaphor and Model-Based Reasoning in Mathematical Physics -- 16.1 Cognitive Tools for Interpretive Understanding -- 16.2 Maxwell's Use of Mathematical Representation -- 16.3 Unpacking the Model-Based Reasoning -- 16.4 Cognition and Metaphor in Mathematical Physics -- 16.5 Conclusions -- References -- 17 Nancy Nersessian's Cognitive-Historical Approach -- 17.1 Questions About the Creation of Scientific Concepts -- 17.2 The Epistemic Virtues of Cognitive Historical Analysis 22.2 Diagrams and (the Philosophy of) Mathematical Practice -- 22.3 The Euclidean Diagram -- 22.4 The Productive Ambiguity of Diagrams -- 22.5 Diagrams in Contemporary Mathematics -- 22.6 Computational Approaches -- 22.7 Mathematical Thinking: Beyond Binary Classifications -- 22.8 Conclusions -- References -- 23 Deduction, Diagrams and Model-Based Reasoning -- 23.1 Euclid's Systematic Use of Geometric Diagrams -- 23.2 Formalizing Euclid's Diagrammatic Proof Method -- 23.3 Formal Geometric Diagrams as Models -- References -- 24 Model-Based Reasoning in Mathematical Practice -- 24.1 Preliminaries -- 24.2 Model-Based Reasoning: Examples -- 24.3 The Power of Heuristics and Plausible Reasoning -- 24.4 Mathematical Fruits of Model-Based Reasoning -- 24.5 Conclusion -- 24.A Appendix -- References -- 25 Abduction and the Emergence of Necessary Mathematical Knowledge -- 25.1 An Example from the Classroom -- 25.2 Inference Types -- 25.3 Abduction in Math and Science Education -- 25.4 Enacting Abductive Action in Mathematical Contexts -- References -- Part F Model-Based Reasoning in Cognitive Science -- 26 Vision, Thinking, and Model-Based Inferences -- 26.1 Inference and Its Modes -- 26.2 Theories of Vision -- 26.3 Stages of Visual Processing -- 26.4 Cognitive Penetrability of Perception and the Relation Between Early Vision and Thinking -- 26.5 Late Vision, Inferences, and Thinking -- 26.6 Concluding Discussion -- 26.A Appendix: Forms of Inferences -- 26.B Appendix: Constructivism -- 26.C Appendix: Bayes' Theorem and Some of Its Epistemological Aspects -- 26.D Appendix: Modal and Amodal Completion or Perception -- 26.E Appendix: Operational Constraints in Visual Processing -- References -- 27 Diagrammatic Reasoning -- 27.1 Cognitive Affordances of Diagrams and Visual Images -- 27.2 Reasoning with Data Graphs -- 27.3 Reasoning with Mechanism Diagrams |
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