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Causal decision theory : ウィキペディア英語版
Causal decision theory
Causal decision theory is a mathematical theory intended to determine the set of rational choices in a given situation. In informal terms, it maintains that the rational choice is that with the best expected causal consequences. This theory is often contrasted with evidential decision theory, which recommends those actions that provide the best evidence about the world.
==Informal Description==

Very informally, causal decision theory advises decision makers to make the decision with the best expected causal consequences. The basic idea is simple enough: if eating an apple will cause you to be happy and eating an orange will cause you to be sad then you would be rational to eat the apple. One complication is the notion of ''expected'' causal consequences. Imagine that eating a good apple will cause you to be happy and eating a bad apple will cause you to be sad but you aren't sure if the apple is good or bad. In this case you don't know the causal effects of eating the apple. Instead, then, you work from the ''expected'' causal effects, where these will depend on three things: (1) how likely you think the apple is to be good and how likely you think it is to be bad; (2) how happy eating a good apple makes you; and (3) how sad eating a bad apple makes you. In informal terms, causal decision theory advises the agent to make the decision with the best expected causal effects.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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