Simulation and Similarity: Using Models to Understand the World (Oxford Studies in the Philosophy of Science), by Michael Weisberg
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Simulation and Similarity: Using Models to Understand the World (Oxford Studies in the Philosophy of Science), by Michael Weisberg
Ebook Download : Simulation and Similarity: Using Models to Understand the World (Oxford Studies in the Philosophy of Science), by Michael Weisberg
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 (Oxford Studies in the Philosophy of Science), by Michael Weisberg- Amazon Sales Rank: #1246251 in Books
- Published on: 2015-10-01
- Released on: 2015-10-01
- Original language: English
- Number of items: 1
- Dimensions: 6.10" h x .50" w x 9.10" l, .0 pounds
- Binding: Paperback
- 212 pages
Review "In my own view, Simulation and Similarity satisfactorily serves such a general purpose, though at a rather formal and abstract level that takes the form of a compilation of advances in meta-theoretical research... For the general reader with a background in the philosophy of science (and I would include here science educators), I see two strong values in the book: (1) it provides a schematic state-of-the-art of semantic stances on what models are and how they can be classified, which is clear and solid, and (2) it contains a careful treatment of (past and present) examples of models and modelling that clarifies theoretical constructs and provides ideas on how to perform good-quality case studies on real instances of scientific modelling, which would be illuminated by those constructs." --Science and Education
"[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."--CHOICEAbout the Author Michael Weisberg is Department Chair and Professor of Philosophy at the University of Pennsylvania.
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Most helpful customer reviews
6 of 6 people found the following review helpful. Outstanding By Irfan A. Alvi Simply put, this is the best book I've yet found on the philosophical aspects of modeling in science (and engineering). The writing is crystal clear and the book should be accessible to non-specialists, yet analytic rigor is also there for those who want it. The author covers uses, development, refinement, and validation of models in sufficient detail and depth to make the book of practical value, not just theoretical value. If you're a 'thinking' modeler (if you develop models, you should be!), this book is a must read.
1 of 1 people found the following review helpful. Models of Modelling - must read for scientists By Netzwerkerin This book is a revelation for anyone using models in a scientific way. It is the first philosophical book I could read without getting stuck at overly complicated sentences, or being hindered by the excessive use of discipline-specific jargon.Weisberg first defends his categorization of three kinds of models (concrete, mathematical, and computational models). He then makes clear that a model is composed of two things (its structure - the thing we normally equate with the model - and its construal). The construal defines 1) the relation between the model and the target system, 2) the intended scope of the model, and 3) its fidelity criteria, i.e., ways to quantify the question of whether the model is good enough to be applied. He then discusses a specific view of mathematical models, called fictions, and dismisses it. He quickly sketches the process of modelling against a given target system, and the three kinds of idealizations we often use in this process (Galilean idealization, minimalist idealization, and multiple models idealization). He also discusses the case, where a model is targetless and shows that it might still be beneficial even if it does not explain any phenomenon of a real-world system. Finally, he introduces a way to measure the goodness of fit of a model, and a way to analyze a model's robustness before he concludes the book with a 3 page summary.Reading the book was very relieving, as my intuition that we are sometimes too fast to apply models to situations where they are not appropriate, can be finally put in scientific terms, namely: in too many cases, the construal is not made explicit and then it can happen that a model is applied outside of its intended scope.I am currently putting bits and pieces of this book in all of my lectures, from "graph theory" to the "fundamentals of programming" to "Complex network analysis", "Formal models of complex systems", and others, because I think that we are sometimes speaking to much about "computers" and too little about "science".I recommend to start the book with the three page summary in the "Conclusion". Since Weisberg avoids using more specific jargon than absolutely necessary, it is well understandable and gives a first conclusive picture of the book. In his introductory pages, he starts with three examples of the three different model types and then developes the story based on these examples bit by bit.
1 of 1 people found the following review helpful. Interesting viewpoint on modeling & simulation By M. Samuels I'm not usually one for philosophy of anything, but this treatise does raise some interesting points about the similarities and differences between analytical modeling, computer simulation and measurement techniques. The discussion of the San Francisco Bay model was fascinating. The comparison of analytical and agent-based approaches would be enhanced if the actual models were available on a CD for experimentation. These are issues I never really thought much about as an engineer; definitely worth reading if modeling & simulation is your thing.
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