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Reliable Reasoning: Induction and Statistical Learning Theory (Jean Nicod Lectures)

Обложка книги Reliable Reasoning: Induction and Statistical Learning Theory (Jean Nicod Lectures)

Reliable Reasoning: Induction and Statistical Learning Theory (Jean Nicod Lectures)

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I had the great priviledge of taking the class upon which this book was based last semester at Princeton University under professors Harman and Kulkarni. It is a fascinating little book, which manages to distill decades of debate and research into concise, readable chapters that carry the presentation forward. The authors' approach is original but commonsensical and they clearly demonstrate the value of interdisciplinary work in their twin fields of philosophy and electrical engineering!

The book is not without its flaws, however. The first chapter seems to take off 'in medias res' expecting the reader to be fully caught up with the latest discussion on the problem of induction, and it is not always clear exactly what a 'process of reasoning' might be compared to deductive arguments. The discussion could have benefited from incorporating material from the other draft textbook we used in class, on "The Nature and Limits of Learning", and even from the lecture handouts. The discussion of simplicity, as well, could have been clarified, especially with regard to Goodman's new riddle of induction and Karl Popper's philosophy of science.

Also rather disappointing in class was the discovery that Harman and Kulkarni's method do not warrant going beyond instrumentalism in scientific theorizing. I was hoping for something a little more robust. In any case, this book should be read by anyone interested in the issues they raise. It sure got me thinking and I will definitely refer to it later on as my research in philosophy brings me in contact again with the issues they discuss.
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