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Induction, Algorithmic Learning Theory, and Philosophy

2007-08-21 Philosophy
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Release : 2007-08-21
Genre : Philosophy
Kind : eBook
Book Rating : 277/5 ( reviews)

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Book Synopsis Induction, Algorithmic Learning Theory, and Philosophy by : Michèle Friend

Download or read book Induction, Algorithmic Learning Theory, and Philosophy written by Michèle Friend. This book was released on 2007-08-21. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to collect essays from philosophers, mathematicians and computer scientists working at the exciting interface of algorithmic learning theory and the epistemology of science and inductive inference. Readable, introductory essays provide engaging surveys of different, complementary, and mutually inspiring approaches to the topic, both from a philosophical and a mathematical viewpoint.

Pluralism in Mathematics: A New Position in Philosophy of Mathematics

2013-11-20 Science
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Release : 2013-11-20
Genre : Science
Kind : eBook
Book Rating : 588/5 ( reviews)

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Book Synopsis Pluralism in Mathematics: A New Position in Philosophy of Mathematics by : Michèle Friend

Download or read book Pluralism in Mathematics: A New Position in Philosophy of Mathematics written by Michèle Friend. This book was released on 2013-11-20. Available in PDF, EPUB and Kindle. Book excerpt: This book is about philosophy, mathematics and logic, giving a philosophical account of Pluralism which is a family of positions in the philosophy of mathematics. There are four parts to this book, beginning with a look at motivations for Pluralism by way of Realism, Maddy’s Naturalism, Shapiro’s Structuralism and Formalism. In the second part of this book the author covers: the philosophical presentation of Pluralism; using a formal theory of logic metaphorically; rigour and proof for the Pluralist; and mathematical fixtures. In the third part the author goes on to focus on the transcendental presentation of Pluralism, and in part four looks at applications of Pluralism, such as a Pluralist approach to proof in mathematics and how Pluralism works in regard to together-inconsistent philosophies of mathematics. The book finishes with suggestions for further Pluralist enquiry. In this work the author takes a deeply radical approach in developing a new position that will either convert readers, or act as a strong warning to treat the word ‘pluralism’ with care.

Philosophy of Computing

2022-05-04 Philosophy
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Release : 2022-05-04
Genre : Philosophy
Kind : eBook
Book Rating : 674/5 ( reviews)

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Book Synopsis Philosophy of Computing by : Björn Lundgren

Download or read book Philosophy of Computing written by Björn Lundgren. This book was released on 2022-05-04. Available in PDF, EPUB and Kindle. Book excerpt: This book features a unique selection of works presented at the 2019 annual international conference of the International Association for Computing and Philosophy (IACAP). Every contribution has been peer-reviewed, revised, and extended. The included chapters are thematically diverse; topics include epistemology, dynamic epistemic logic, topology, philosophy of science and computation, game theory and abductive inferences, automated reasoning and mathematical proofs, computer simulations, scientific modelling, applied ethics, pedagogy, human-robot interactions, and big data, algorithms, and artificial intelligence. The volume is a testament to the value of interdisciplinary approaches to the computational and informational turn. We live in a time of tremendous development, which requires rigorous reflection on the philosophical nature of these technologies and how they are changing the world. How can we understand these technologies? How do these technologies change our understanding of the world? And how do these technologies affect our place as humans in the world? These questions, and more, are addressed in this volume which is of interest to philosophers, engineers, and computer scientists alike.

Algorithmic Learning Theory

2015-10-04 Computers
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Release : 2015-10-04
Genre : Computers
Kind : eBook
Book Rating : 868/5 ( reviews)

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Book Synopsis Algorithmic Learning Theory by : Kamalika Chaudhuri

Download or read book Algorithmic Learning Theory written by Kamalika Chaudhuri. This book was released on 2015-10-04. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 26th International Conference on Algorithmic Learning Theory, ALT 2015, held in Banff, AB, Canada, in October 2015, and co-located with the 18th International Conference on Discovery Science, DS 2015. The 23 full papers presented in this volume were carefully reviewed and selected from 44 submissions. In addition the book contains 2 full papers summarizing the invited talks and 2 abstracts of invited talks. The papers are organized in topical sections named: inductive inference; learning from queries, teaching complexity; computational learning theory and algorithms; statistical learning theory and sample complexity; online learning, stochastic optimization; and Kolmogorov complexity, algorithmic information theory.

Hume's Problem Solved

2019-05-07 Philosophy
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Release : 2019-05-07
Genre : Philosophy
Kind : eBook
Book Rating : 451/5 ( reviews)

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Book Synopsis Hume's Problem Solved by : Gerhard Schurz

Download or read book Hume's Problem Solved written by Gerhard Schurz. This book was released on 2019-05-07. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to Hume's problem of induction that justifies the optimality of induction at the level of meta-induction. Hume's problem of justifying induction has been among epistemology's greatest challenges for centuries. In this book, Gerhard Schurz proposes a new approach to Hume's problem. Acknowledging the force of Hume's arguments against the possibility of a noncircular justification of the reliability of induction, Schurz demonstrates instead the possibility of a noncircular justification of the optimality of induction, or, more precisely, of meta-induction (the application of induction to competing prediction models). Drawing on discoveries in computational learning theory, Schurz demonstrates that a regret-based learning strategy, attractivity-weighted meta-induction, is predictively optimal in all possible worlds among all prediction methods accessible to the epistemic agent. Moreover, the a priori justification of meta-induction generates a noncircular a posteriori justification of object induction. Taken together, these two results provide a noncircular solution to Hume's problem. Schurz discusses the philosophical debate on the problem of induction, addressing all major attempts at a solution to Hume's problem and describing their shortcomings; presents a series of theorems, accompanied by a description of computer simulations illustrating the content of these theorems (with proofs presented in a mathematical appendix); and defends, refines, and applies core insights regarding the optimality of meta-induction, explaining applications in neighboring disciplines including forecasting sciences, cognitive science, social epistemology, and generalized evolution theory. Finally, Schurz generalizes the method of optimality-based justification to a new strategy of justification in epistemology, arguing that optimality justifications can avoid the problems of justificatory circularity and regress.

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