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Science in the Age of Computer Simulation

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Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenom Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Eric Winsberg seeks to answer these questions in Science in the Age of Computer Simulation. Scrutinizing these issue with a philosophical lens, Winsberg explores the impact of simulation on such issues as the nature of scientific evidence; the role of values in science; the nature and role of fictions in science; and the relationship between simulation and experiment, theories and data, and theories at different levels of description. Science in the Age of Computer Simulation will transform many of the core issues in philosophy of science, as well as our basic understanding of the role of the digital computer in the sciences.


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Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenom Computer simulation was first pioneered as a scientific tool in meteorology and nuclear physics in the period following World War II, but it has grown rapidly to become indispensible in a wide variety of scientific disciplines, including astrophysics, high-energy physics, climate science, engineering, ecology, and economics. Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Eric Winsberg seeks to answer these questions in Science in the Age of Computer Simulation. Scrutinizing these issue with a philosophical lens, Winsberg explores the impact of simulation on such issues as the nature of scientific evidence; the role of values in science; the nature and role of fictions in science; and the relationship between simulation and experiment, theories and data, and theories at different levels of description. Science in the Age of Computer Simulation will transform many of the core issues in philosophy of science, as well as our basic understanding of the role of the digital computer in the sciences.

30 review for Science in the Age of Computer Simulation

  1. 4 out of 5

    Isaac

    This book collects the essays Winsberg has published over the last decade or so (they can be found separately on PhilPapers, but the collection does have a new introduction. Either way you read it, it's some of the best recent work on simulations, and is important for philosophers of science and practically-minded epistemologists. This book collects the essays Winsberg has published over the last decade or so (they can be found separately on PhilPapers, but the collection does have a new introduction. Either way you read it, it's some of the best recent work on simulations, and is important for philosophers of science and practically-minded epistemologists.

  2. 5 out of 5

    Andrew

    New words that I did learn: "reify", "mereological". I shall endeavor to make use of them in everyday conversation forthwith. New words that I did learn: "reify", "mereological". I shall endeavor to make use of them in everyday conversation forthwith.

  3. 4 out of 5

    Paweł

    Misleading title.

  4. 5 out of 5

    Ansh Shukla

    I read this book without having any prior familiarity with the philosophy of science and limited exposure to philosophy in general. As such, making it through each page was fairly painful. I do not know whether this should be viewed as an accomplishment (research papers which are also approachable, with effort, for the layman) or a failure (unnecessarily abstruse). I thought the ideas developed in the book were relevant to other fields of computing, and they were introduced in a systematic enough I read this book without having any prior familiarity with the philosophy of science and limited exposure to philosophy in general. As such, making it through each page was fairly painful. I do not know whether this should be viewed as an accomplishment (research papers which are also approachable, with effort, for the layman) or a failure (unnecessarily abstruse). I thought the ideas developed in the book were relevant to other fields of computing, and they were introduced in a systematic enough way that I've mentally developed analogues to my own work. The rigorous look at model building as a new, independent, and uncertain mode of science was fascinating. It was fun to finish and a good length.

  5. 5 out of 5

    Dallas Clement

  6. 4 out of 5

    Jan Kwakkel

  7. 4 out of 5

    Nick

  8. 4 out of 5

    Edwin

  9. 5 out of 5

    Adam Koberinski

  10. 5 out of 5

    Alex

  11. 5 out of 5

    OLEG SMIRNOV

  12. 5 out of 5

    Joe Gibbs

  13. 4 out of 5

    Ash Jogalekar

  14. 5 out of 5

    Radin

  15. 5 out of 5

    Jayson Vavrek

  16. 4 out of 5

    Mostafa Fahmy

  17. 5 out of 5

    jc

  18. 5 out of 5

    Marco

  19. 4 out of 5

    Eric

  20. 5 out of 5

    Jeff Walls

  21. 5 out of 5

    Zombie Reagan

  22. 4 out of 5

    Adeel Yawar Jamil

  23. 4 out of 5

    Alex Gurvich

  24. 4 out of 5

    Abikoye Olufemi

  25. 4 out of 5

    Sarah

  26. 4 out of 5

    Kevin Zollman

  27. 5 out of 5

    Sunil

  28. 5 out of 5

    Ben Keller

  29. 5 out of 5

    Raymond B.

  30. 4 out of 5

    David

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