More New and Used
from Private Sellers
Note: Supplemental materials are not guaranteed with Rental or Used book purchases.
Questions About This Book?
What version or edition is this?
This is the edition with a publication date of 2/7/2013.
What is included with this book?
- The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any CDs, lab manuals, study guides, etc.
Brian Skyrms presents a set of influential essays on the nature of quantity, probability, coherence, and induction. The first part explores the nature of quantity and includes essays on tractarian nominalism, combinatorial possibility, and coherence. Part Two proceeds to examine coherent updating of degrees of belief in various learning situations. Finally, in Part Three, Skyrms develops an account of aspects of inductive reasoning, which proceeds from specific problems to generalconsiderations. These essays span the breadth of Skyrms's illustrious career and will be essential reading for scholars and advanced students in philosophy of science and formal epistemology.
Brian Skyrms is Distinguished Professor of Logic and Philosophy of Science and Economics at the University of California, Irvine. His interests cover a range of topics, including the evolution of conventions, the social contract, inductive logic, decision theory, rational deliberation, the metaphysics of logical atomism, causality, and truth. He is the author of Signals: Evolution, Learning, and Information (OUP, 2010).
Table of Contents
I. Zeno and the Metaphysics of Quantity
1. Zeno's Paradox of Measure
2. Tractarian Nominalism
3. Logical Atoms and Combinatorial Possibility
4. Strict Coherence, Sigma Coherence, and the Metaphysics of Quantity
II. Coherent Degrees of Belief
5. Higher Order Degrees of Belief
6. A Mistake in Dynamic Coherence Arguments?
7. Dynamic Coherence and Probability Kinematics
8. Updating, Supposing, and MAXENT
9. The Structure of Radical Probabilism
10. Diachronic Coherence and Radical Probabilism
11. Carnapian Inductive Logic for Markov Chains
12. Carnapian Inductive Logic and Bayesian Statistics
13. Bayesian Projectibility