Characterising Decision Theories with Mechanised Causal Graphs

• URL: http://arxiv.org/abs/2307.10987v1
• Date: Thu, 20 Jul 2023 16:18:22 GMT
• Title: Characterising Decision Theories with Mechanised Causal Graphs
• Authors: Matt MacDermott, Tom Everitt, and Francesco Belardinelli
• Abstract summary: We show that mechanised causal models can be used to characterise and differentiate the most important decision theories. We generate a taxonomy of different decision theories.
• Score: 11.114498728830851
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: How should my own decisions affect my beliefs about the outcomes I expect to achieve? If taking a certain action makes me view myself as a certain type of person, it might affect how I think others view me, and how I view others who are similar to me. This can influence my expected utility calculations and change which action I perceive to be best. Whether and how it should is subject to debate, with contenders for how to think about it including evidential decision theory, causal decision theory, and functional decision theory. In this paper, we show that mechanised causal models can be used to characterise and differentiate the most important decision theories, and generate a taxonomy of different decision theories.

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