Simulation and similarity : using models to understand the world / Michael Weisberg.

Format:

Book

Author/Creator:

Weisberg, Michael, 1976-

Series:

Oxford studies in philosophy of science

Language:

English

Subjects (All):

Science--Mathematical models--Philosophy.

Science.

Science--Mathematical models.

Philosophy.

Physical Description:

xviii, 190 pages : illustrations, map ; 25 cm.

Place of Publication:

New York : Oxford University Press, [2013]

Summary:

Simulation and Similarity is an account of modeling and idealization in modern scientific practice, focusing on concrete, mathematical, and computational models. The main topics of this book are the nature of models, the practice of modeling, and the nature of the relationship between models and real-world phenomena. In order to elucidate the model/world relationship, Weisberg develops a novel account of similarity called weighted feature matching.

Contents:

1 Introduction 1

1.1 Two Aquatic Puzzles 1

1.2 Models of Modeling 4

2 Three Kinds of Models 7

2.1 Concrete Model: The San Francisco Bay-Delta Model 7

2.2 Mathematical Model: Lotka-Volterra Model 10

2.3 Computational Model: Schelling's Segregation Model 13

2.4 Common Features of these Models 14

2.5 Only Three Types of Models? 15

2.6 Fewer than Three Types of Model? 19

3 The Anatomy of Models 24

3.1 Structure 24

3.1.1 Concrete Structures 24

3.1.2 Mathematical Structures 25

3.1.3 Computational Structures 29

3.2 Model Descriptions 31

3.3 Construal 39

3.4 Representational Capacity of Structures 42

4 Fictions and Folk Ontology 46

4.1 Against Maths: Individuation, Causes, and Face-Value Practice 46

4.2 A Simple Fictions Account 49

4.3 Enriching the Simple Account 51

4.3.1 Waltonian Fictionalism 53

4.3.2 Fictions Without Models 55

4.4 Why I Am Not a Fictionalist 56

4.4.1 Variation 56

4.4.2 Representational Capacity of Different Models 61

4.4.3 Making Sense of Modeling 63

4.4.4 Variation in Practice 64

4.5 Folk Ontology 67

4.6 Maths, Interpretation, and Folk Ontology 70

5 Target-Directed Modeling 74

5.1 Model Development 75

5.2 Analysis of the Model 79

5.2.1 Complete Analysis 79

5.2.2 Goal-Directed Analysis 83

5.3 Model-Target Comparison 90

5.3.1 Phenomena and Target Systems 90

5.3.2 Establishing the Fit between Model and Target 93

5.3.3 Representations of Targets 95

6 Idealization 98

6.1 Three Kinds of Idealization 98

6.1.1 Galilean Idealization 99

6.1.2 Minimalist Idealization 100

6.1.3 Multiple-Models Idealization 103

6.2 Representational Ideals and Fidelity Criteria 105

6.2.1 Completeness 105

6.2.2 Simplicity 107

6.2.3 1-Causal 107

6.2.4 Maxout 109

6.2.5 P-General 109

6.3 Idealization and Representational Ideals 110

6.4 Idealization and Target-Directed Modeling 112

7 Modeling Without a Specific Target 114

7.1 Generalized Modeling 114

7.1.1 How-Possibly Explanations 118

7.1.2 Minimal Models and First-Order Causal Structures 119

7.2 Hypothetical Modeling 121

7.2.1 Contingent Nonexistence: xDNA 122

7.2.2 Impossible Targets: Infinite Population Growth and Perpetual Motion 124

7.3 Targetless Modeling 129

7.4 A Moving Target: The Case of Three-sex Biology 131

8 An Account of Similarity 135

8.1 Desiderata for Model-World Relations 135

8.2 Model-Theoretic Accounts 137

8.3 Similarity 142

8.4 Tversky's Contrast Account 143

8.5 Attributes and Mechanisms 145

8.6 Feature Sets, Construals, and Target Systems 148

8.7 Modeling Goals and Weighting Parameters 150

8.8 Weighting Function and Background Theory 152

8.9 Satisfying the Desiderata 154

9 Robustness Analysis and Idealization 156

9.1 Levins and Wimsatt on Robustness 156

9.2 Finding Robust Theorems 158

9.3 Three Kinds of Robustness 159

9.3.1 Parameter Robustness 160

9.3.2 Structural Robustness 161

9.3.3 Representational Robustness 162

9.4 Robustness and Confirmation 167

10 Conclusion: The Practice of Modeling 171.

Notes:

Includes bibliographical references (pages 176-185).

ISBN:

9780199933662

0199933669

9780199933679

0199933677

OCLC:

800445416