Reliable Reasoning
Induction and Statistical Learning Theory
By Gilbert Harman, Sanjeev Kulkarni | Publisher: MIT Press
About the book
The implications for philosophy and cognitive science of developments in statistical learning theory.
In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT.
After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.
Editions of Reliable Reasoning
- Hardcover
- ISBN 9780262083607
- Paperback
- ISBN 9780262517348
- EBook
- ISBN 9780262252218
- EBook
- ISBN 9780262263153
- EBook
- ISBN 9780262274975
Read an Excerpt
The implications for philosophy and cognitive science of developments in statistical learning theory.
In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT.
After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.
Frequently Asked Questions
What is Reliable Reasoning about?
The implications for philosophy and cognitive science of developments in statistical learning theory.
In Reliable Reasoning, Gilbert Harman and Sanjeev Kulkarni—a philosopher and an engineer—argue that philosophy and cognitive science can benefit from statistical learning theory (SLT), the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors—a central topic in SLT.
After discussing philosophical attempts to evade the problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis (VC) dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT.
What core themes, tropes, or subjects are explored in Reliable Reasoning?
Society and Social Sciences > Psychology > Cognition and cognitive psychology
Where can I read a sample of Reliable Reasoning?
You can read an official preview of the few pages here https://www.book2look.com/book/9780262083607
Is Reliable Reasoning part of a series, and can it be read as a standalone?
Yes it is a part of series Jean Nicod Lectures
Who is/are the Author/s of the book Reliable Reasoning?
Gilbert Harman, Sanjeev Kulkarni
Who is the Publisher of the book Reliable Reasoning?
MIT Press
What are the ISBN numbers for the physical and digital editions?
Reliable Reasoning is available as hardcover(ISBN 9780262083607) and paperback(ISBN 9780262517348) and ebook(ISBN 9780262252218) and ebook(ISBN 9780262263153) and ebook(ISBN 9780262274975)
Where can I buy Reliable Reasoning online or support local independent bookshops?
You can buy Reliable Reasoning from below
Where can I buy Reliable Reasoning?