Simulation and Similarity

Using Models to Understand the World

Michael Weisberg

Oxford Studies in Philosophy of Science

The book offers a comprehensive new account of scientific models and modeling. Whereas most other treatments only deal with mathematical models, this book deals with physical (concrete), mathematical, and computational models.
The most novel part of the book is a new theory of similarity, which is offered as an account of the relationship between models and the world.

Simulation and Similarity

Using Models to Understand the World

Michael Weisberg

Oxford Studies in Philosophy of Science

Description

In the 1950s, John Reber convinced many Californians that the best way to solve the state's water shortage problem was to dam up the San Francisco Bay. Against massive political pressure, Reber's opponents persuaded lawmakers that doing so would lead to disaster. They did this not by empirical measurement alone, but also through the construction of a model. Simulation and Similarity explains why this was a good strategy while simultaneously providing an account of modeling and idealization in modern scientific practice. Michael Weisberg focuses on concrete, mathematical, and computational models in his consideration of the nature of models, the practice of modeling, and nature of the relationship between models and real-world phenomena.

In addition to a careful analysis of physical, computational, and mathematical models, Simulation and Similarity offers a novel account of the model/world relationship. Breaking with the dominant tradition, which favors the analysis of this relation through logical notions such as isomorphism, Weisberg instead presents a similarity-based account called weighted feature matching. This account is developed with an eye to understanding how modeling is actually practiced. Consequently, it takes into account the ways in which scientists' theoretical goals shape both the applications and the analyses of their models.

Simulation and Similarity

Using Models to Understand the World

Michael Weisberg

Oxford Studies in Philosophy of Science

Contents
Preface
1 Introduction
1.1 Two Aquatic Puzzles
1.2 Models of Modeling
2 Three Kinds of Models
2.1 Concrete Model: The San Francisco Bay-Delta Model
2.2 Mathematical Model: Lotka-Volterra Model
2.3 Computational Model: Schelling's Segregation Model
2.4 Common Features of these Models
2.5 Only Three Types of Models?
2.6 Fewer Than Three Types of Model?
3 The Anatomy of Models: Structure & Construal
3.1 Structure
3.1.1 Concrete Structures
3.1.2 Mathematical
3.1.3 Computational
3.2 Model Descriptions
3.3 Construal
3.4 Representational Capacity of Structures
4 Fictions and Folk Ontology
4.1 Against Maths: Individuation, Causes, and Face Value Practice
4.2 A Simple Fictions Account
4.3 Enriching the Simple Account
4.3.1 Waltonian Fictionalism
4.3.2 Fictions without Models
4.4 Why I am not a Fictionalist
4.4.1 Variation
4.4.2 Representational Capacity of Different Models
4.4.3 Making Sense of Modeling
4.4.4 Variation in Practice
4.5 Folk ontology
4.6 Maths, Interpretation, and Folk Ontology
5 Target Directed Modeling
5.1 Model Development
5.2 Analysis of the Model
5.2.1 Complete Analysis
5.2.2 Goal-directed Analysis
5.3 Model/Target Comparison
5.3.1 Phenomena and Target Systems
5.3.2 Establishing the fit between Model and Target
5.3.3 Representations of Targets
6 Idealization
6.1 Three Kinds of Idealization
6.1.1 Galilean idealization
6.1.2 Minimalist idealization
6.1.3 Multiple Models Idealization
6.2 Representational Ideals and Fidelity Criteria
6.2.1 Completeness
6.2.2 Simplicity
6.2.3 1-Causal
6.2.4 Maxout
6.2.5 P-General
6.3 Idealization and Representational Ideals
6.4 Idealization and Target Directed Modeling
7 Modeling Without a Specific Target
7.1 Generalized Modeling
7.1.1 How Possibly Explanations
7.1.2 Minimal Models and First Order Causal Structures
7.2 Hypothetical Modeling
7.2.1 Contingent Non-existence: xDNA
7.2.2 Impossible Targets: Infinite Population Growth and Perpetual Motion
7.3 Targetless Modeling
7.4 A Moving Target: The Case of Three-sex Biology
8 An Account of Similarity
8.1 Desiderata for Model/World Relations
8.2 Model Theoretic Accounts
8.3 Similarity
8.4 Tversky's Contrast Account
8.5 Attributes and Mechanisms
8.6 Feature Sets, Construals, and Target Systems
8.7 Modeling Goals and Weighting Parameters
8.8 Weighting Function and Background Theory
8.9 Satisfying the Desiderata
9 Robustness Analysis and Idealization
9.1 Levins and Wimsatt on Robustness
9.2 Finding Robust Theorems
9.3 Three Kinds of Robustness
9.3.1 Parameter Robustness
9.3.2 Structural Robustness
9.3.3 Representational Robustness
9.4 Robustness and Confirmation
10 Conclusion: The Practice of Modeling
References

Simulation and Similarity

Using Models to Understand the World

Michael Weisberg

Oxford Studies in Philosophy of Science

Author Information

Michael Weisberg, Associate Professor and Graduate Chair of Philosophy, University of Pennsylvania, USA

Michael Weisberg is Associate Professor of Philosophy at the University of Pennsylvania.

Simulation and Similarity

Using Models to Understand the World

Michael Weisberg

Oxford Studies in Philosophy of Science

Reviews and Awards

"Michael Weisberg has given us a lovely book on models. It has very broad coverage of issues intersecting the nature of models and their use, an extensive consideration of long ignored concrete models with a rich case study, a discussion and classification of the many diverse kinds of models, and a particularly groundbreaking and innovative discussion of similarity concerning how models relate to the world ... his analysis is both clear and rich." - William C. Wimsatt, Biology and Philosophy

"[This book] is lively, well-written, and should be accessible to novice audiences as well as informative and provocative to disciplinary insiders. It skillfully makes use of a relatively small set of carefully explained and not-overly-complicated examples to give an account that succeeds in being sophisticated and attentive to the details of scientific practice without getting overly mired in the details of 'case studies' that sometimes plague the literature on scientific modeling." - Eric Winsberg, Notre Dame Philosophical Reviews

"[Simulation and Similarity] is well written and detailed in its exposition, providing concrete examples to ground the discussion. It is a very interesting complement to standard mathematical modeling treatments for scientists, engineers, and mathematicians." - R. A. Kolvoord, CHOICE

"The book provides a useful and intuitive classification of kinds of models, kinds of modelling methodologies, and model components that is sensitive to the diversity of scientific practice." - Michael Weisberg, The British Journal for the Philosophy of Science

"...a compelling account of models and can be highly recommended to philosophers of science as well as to scientists of any particular discipline, especially those practicing modeling and simulation in their everydays work." - V. S. Pronskikh, Metascience