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The Stanford Encyclopedia of Philosophy has a nice overview of numerous different interpretations of probability (classical as opposed to quantum) with an extensive bibliography.

What books would serve as well-balanced, objective overviews of this topic for the reader with at least a firm grasp of Bayes' Theorem and the basics of Kolmogorov's axioms?

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    $\begingroup$ That article recommends Terrence Fine’s 1973 book, Theories of Probability, and I concur. $\endgroup$
    – user44143
    Commented Aug 18, 2019 at 2:31
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    $\begingroup$ I suggest learning some probability, as in Feller volume 1, instead. $\endgroup$ Commented Aug 18, 2019 at 6:20
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    $\begingroup$ Feller's book is of course an excellent book on probability theory, but I'm not sure it is very helpful to the person wanting to understand interpretations of probability. Very little technical knowledge is necessary for that. $\endgroup$ Commented Aug 18, 2019 at 10:49
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    $\begingroup$ Mathematicians generally do not like discussing philosophical aspects of probability, or its relation to the so-called "real world". A rare exception is the Russian textbook by Tutubalin which I read in my youth, unfortunately I do not know its translations to any other languages. Other good accounts by mathematicians are A. Renyi, Letters on Probability and E. Borel, Probability and certainty. $\endgroup$ Commented Aug 18, 2019 at 18:21
  • $\begingroup$ Decades ago I did some reading on different interpretations, sometime after I had studied quantum and classical statistical mech in college. Fine, Borel, Jaynes, Keynes, and Ruelle are some authors whose writings on the topic I at least perused as well as Khaneman and Tversky. There were others, but my library suffered a catastrophe, so I have no more notes. This question is really for those advanced undergrad and grad students who might benefit from/appreciate understanding the diversity of schools of thought and passions in this field. All contributions to this post are appreciated. $\endgroup$ Commented Aug 19, 2019 at 19:39

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From the webpage for Persi Diaconis and Brian Skyrms, Ten Great Ideas about Chance:

In the sixteenth and seventeenth centuries, gamblers and mathematicians transformed the idea of chance from a mystery into the discipline of probability, setting the stage for a series of breakthroughs that enabled or transformed innumerable fields, from gambling, mathematics, statistics, economics, and finance to physics and computer science. This book tells the story of ten great ideas about chance and the thinkers who developed them, tracing the philosophical implications of these ideas as well as their mathematical impact.

Persi Diaconis and Brian Skyrms begin with Gerolamo Cardano, a sixteenth-century physician, mathematician, and professional gambler who helped develop the idea that chance actually can be measured. They describe how later thinkers showed how the judgment of chance also can be measured, how frequency is related to chance, and how chance, judgment, and frequency could be unified. Diaconis and Skyrms explain how Thomas Bayes laid the foundation of modern statistics, and they explore David Hume’s problem of induction, Andrey Kolmogorov’s general mathematical framework for probability, the application of computability to chance, and why chance is essential to modern physics. A final idea—that we are psychologically predisposed to error when judging chance—is taken up through the work of Daniel Kahneman and Amos Tversky.

Complete with a brief probability refresher, Ten Great Ideas about Chance is certain to be a hit with anyone who wants to understand the secrets of probability and how they were discovered.

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