Book contents
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Introduction: Bayesian decision theory – foundations and problems
- Part I Foundations of Bayesian decision theory
- Part II Conceptualization of probability and utility
- Part III Questionable rules of rationality
- Part IV Unreliable probabilities
- Part V Causal decision theory
- References
- Name index
- Subject index
Part V - Causal decision theory
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- List of contributors
- Preface
- 1 Introduction: Bayesian decision theory – foundations and problems
- Part I Foundations of Bayesian decision theory
- Part II Conceptualization of probability and utility
- Part III Questionable rules of rationality
- Part IV Unreliable probabilities
- Part V Causal decision theory
- References
- Name index
- Subject index
Summary
Ingenious problems which cannot be properly handled by the traditional decision theory form an obvious basis for developments of the theory. Earlier in the volume we have seen how the “paradoxes” introduced by Allais and Ellsberg have led to lively discussions and fruitful investigations. In the present part a new line of development will be presented, namely causal decision theory. This theory derives from the following decision problem:
Newcomb's problem. In front of you on the table are two boxes. One box is transparent and you can see that it contains $1000. The other box is opaque, but you are told that it contains $1,000,000 ($1M) or nothing ($0). You have two choice alternatives: Take the opaque box only or take both boxes. The hook is that what is in the opaque box is determined by a gifted person who is a very reliable predictor of your behavior: If he predicts that you will take only the opaque box, he will put a million dollars in it; however, if he predicts that you will take both boxes, then he puts nothing in the opaque box. The person makes his prediction prior to your choice, i.e., when you decide the content of the opaque box is already determined. But you also know that the person is almost a perfect predictor of your behavior and has proved very successful in predicting other people's behavior in similar situations.
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- Information
- Decision, Probability and UtilitySelected Readings, pp. 335 - 340Publisher: Cambridge University PressPrint publication year: 1988