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Structural Decision Theory

Wu, Tung-Ying (2020) Structural Decision Theory. In: UNSPECIFIED.

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Abstract

Judging an act’s causal efficacy plays a crucial role in causal decision theory. A recent development appeals to the causal modeling framework with an emphasis on the analysis of intervention based on the causal Bayes net for clarifying what causally depends on our acts. However, few writers have focused on exploring the usefulness of extending structural causal models to decision problems that are not ideal for intervention analysis. I found that it is structural models, rather than intervention analysis, serves as a valuable formal tool for a range of realistic decision problems that involve mixed causal mechanisms. The thesis concludes that structural models provide a more general framework for rational decision-makers.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Creators:
CreatorsEmailORCID
Wu, Tung-Yingtungyingwu@outlook.com0000-0001-9839-7584
Additional Information: This is an early draft to be presented at: The 27th Biennial Meeting of the Philosophy of Science Association, 2020, Baltimore, MD. Please do not cite or quote without permission. Any criticisms or suggestions are welcome. Contact Email: tungyingwu@outlook.com
Keywords: causal decision theory, causal Bayes net, interventionist, structural causal models
Subjects: General Issues > Causation
General Issues > Decision Theory
Depositing User: TUNG-YING WU
Date Deposited: 08 Jul 2020 02:49
Last Modified: 08 Jul 2020 02:49
Item ID: 17442
Subjects: General Issues > Causation
General Issues > Decision Theory
Date: 2020
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/17442

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