Taking Chances

J. Howard Sobel has long been recognized as an important figure in philosophical discussions of rational decision. He has done much to help formulate the concept of causal decision theory. In this volume of essays Sobel explores the Bayesian idea that rational actions maximize expected values, where an action\'s expected value is a weighted average of its agent\'s values for its possible total outcomes. Newcomb’s Problem and The Prisoner’s Dilemma are discussed, and Allais-type puzzles are viewed from the perspective of causal world Bayesianism. The author establishes principles for distinguishing options in decision problems, and studies ways in which perfectly rational causal maximizers can be capable of resolute choices. Sobel also views critically Gauthier’s revisionist ideas about maximizing rationality. This collection will be a desideratum for anyone working in the field of rational choice theory, whether in philosophy, economics, political science, psychology or statistics. Howard Sobel’s work in decision theory is certainly among the most important, interesting and challenging that is being done by philosophers.

• Major philosopher working in decision theory - this collection represents his most important publishing in the field • Genuine interdisciplinary interest in economics, statistics, political science and psychology

Preface; Part I. World Bayesianism: 1. Utility and the Bayesian paradigm; Part II. Problems for Evidential Decision Theory: 2. Newcomblike problems; 3. Not every prisoners\' dilemma is a Newcomb problem; 4. Some versions of Newcomb’s problem are prisoners\' dilemmas; 5. Infallible predictors; 6. Kent Bach on good arguments; 7. Maximising and prospering; Part III. Causal Decision Theory: 8. Notes on decision theory: old wine in new bottles; 9. Partition theorems for causal decision theories; 10. Expected utilities and rational actions and choices; 11. Maximisation, stability of decision and actions in accordance with reason; 12. Useful intentions; Part IV. Interacting Causal Maximisers: 13. The need for coercion; 14. Hyperrational games; 15. Utility maximizers in iterated prisoners\' dilemmas; 16. Backward induction arguments: a paradox regained; References; Index of names.