Simulation and Similarity: Using Models to Understand the World
Simulation and Similarity: Using Models to Understand the World
Associate Professor and Graduate Chair of Philosophy
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Abstract
In the 1950s John Reber convinced many Californians that the best way to solve the state’s water shortages was to dam up the San Francisco Bay. Against massive political pressure, his opponents convinced lawmakers that this would lead to disaster—not by empirical measurement alone, but by constructing a model. Simulation and Similarity explains why this was a good strategy. It provides an account of modeling and idealization in modern scientific practice, focusing on concrete, mathematical, and computational models. The book has three main themes: the nature of models, the practice of modeling, and nature of the relationship between models and real-world phenomena. In addition to its careful analysis of physical, computational, and mathematical models, one of Simulation and Similarity’s most novel features is Weisberg’s account of the model–world relationship. Breaking with the dominant tradition, which says this relation should be analyzed using logical notions such as isomorphism, Weisberg presents a similarity-based account called weighted feature-matching. This account of the model–world relationship is developed with an eye to understanding how modeling is actually practiced, hence it takes into account how scientists’ theoretical goals shape the ways in which their models are applied and analyzed.
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Front Matter
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1
Introduction
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2
Three Kinds of Models
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3
The Anatomy of Models
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4
Fictions and Folk Ontology
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5
Target-Directed Modeling
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6
Idealization
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7
Modeling Without a Specific Target
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8
An Account of Similarity
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9
Robustness Analysis and Idealization
- 10 Conclusion: The Practice — of Modeling
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End Matter
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