An Introduction to Decision Theory 2nd edition by Martin Peterson – Ebook PDF Instant Download/Delivery: 1316606201 , 978-1316606209
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ISBN 10: 1316606201
ISBN 13: 978-1316606209
Author: Martin Peterson
Now revised and updated, this introduction to decision theory is both accessible and comprehensive, covering topics including decision making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory, and social choice theory. No mathematical skills are assumed, with all concepts and results explained in non-technical and intuitive as well as more formal ways. There are now over 140 exercises with solutions, along with a glossary of key terms and concepts. This second edition includes a new chapter on risk aversion as well as updated discussions of numerous central ideas, including Newcomb’s problem, prisoner’s dilemmas, and Arrow’s impossibility theorem. The book will appeal particularly to philosophy students but also to readers in a range of disciplines, from computer science and psychology to economics and political science.
An Introduction to Decision Theory 2nd Table of contents:
1 Introduction
1.1 Normative and Descriptive Decision Theory
1.2 Rational and Right Decisions
1.3 Risk, Ignorance and Uncertainty
1.4 Social Choice Theory and Game Theory
1.5 A Very Brief History of Decision Theory
2 The Decision Matrix
2.1 States
2.2 Outcomes
2.3 Acts
2.4 Rival Formalizations
3 Decisions under Ignorance
3.1 Dominance
3.2 Maximin and Leximin
3.3 Maximax and the Optimism–Pessimism Rule
3.4 Minimax Regret
3.5 The Principle of Insufficient Reason
3.6 Randomized Acts
4 Decisions under Risk
4.1 Maximizing What?
4.2 Why is it Rational to Maximize Expected Utility?
4.3 The Axiomatic Approach
4.4 The Allais Paradox
4.5 The Ellsberg Paradox
4.6 The St. Petersburg Paradox
4.7 The Pasadena Paradox
4.8 The Two-Envelope Paradox
5 Utility
5.1 How to Construct an Ordinal Scale
5.2 Von Neumann and Morgenstern’s Interval Scale
5.3 Can Utility be Measured on a Ratio Scale?
5.4 Can We Define Utility Without Being Able to Measure It?
6 The Mathematics of Probability
6.1 The Probability Calculus
6.2 Conditional Probability
6.3 Bayes’ Theorem
6.4 The Problem of Unknown Priors
7 The Philosophy of Probability
7.1 The Classical Interpretation
7.2 The Frequency Interpretation
7.3 The Propensity Interpretation
7.4 Logical and Epistemic Interpretations
7.5 Subjective Probability
7.5.1 State-dependent Utilities
7.5.2 The Dutch Book Theorem
7.5.3 Minimal Subjectivism
8 Bayesianism and Pragmatic Arguments
8.1 Why Should We Accept the Axioms?
8.2 Must a Rational Preference be Transitive?
8.3 Must a Rational Preference be Complete?
8.4 Must a Rational Preference Satisfy the Independence Axiom?
8.5 Can Bayesians be Money Pumped?
8.6 Do Bayesians Put the Cart Before the Horse?
8.7 Non-Bayesian Decision Theory
9 Causal vs. Evidential Decision Theory
9.1 Newcomb’s Problem
9.2 Causal Decision Theory
9.3 Evidential Decision Theory
10 Risk Aversion
10.1 Actuarial Risk Aversion
10.2 Aversion Against Utility Risks
10.3 Epistemic Risk Aversion
11 Game Theory I: Basic Concepts and Zero-sum Games
11.1 The Prisoner’s Dilemma
11.2 A Taxonomy of Games
11.3 Common Knowledge and Dominance Reasoning
11.4 Two-Person Zero-sum Games
11.5 Mixed Strategies and the Minimax Theorem
12 Game Theory II: Nonzero-sum and Cooperative Games
12.1 The Nash Equilibrium
12.2 The Battle of the Sexes and Chicken
12.3 The Bargaining Problem
12.4 Iterated Games
12.5 Game Theory and Evolution
12.6 Game Theory and Ethics
13 Social Choice Theory
13.1 The Social Choice Problem
13.2 Arrow’s Impossibility Theorem
13.3 Sen on Liberalism and the Pareto Principle
13.4 Harsanyi’s Utilitarian Theorems
14 Overview of Descriptive Decision Theory
14.1 Observed Violations of the Expected Utility Principle
14.2 Prospect Theory
14.3 Violations of Transitivity and Completeness
14.4 The Relevance of Descriptive Decision Theory
Appendix: Glossary
Further Reading
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