Functional Decision Theory: A New Theory of Instrumental Rationality

By Eliezer Yudkowsky, Nate Soares. 2017

51 citations recorded by the source corpus.

This paper describes and motivates a new decision theory known as functional decision theory (FDT), as distinct from causal decision theory and evidential decision theory. Functional decision theorists hold that the normative principle for action is to treat one's decision as the output of a fixed mathematical function that answers the question, "Which output of this very function would yield the best outcome?" Adhering to this principle delivers a number of benefits, including the ability to maximize wealth in an array of traditional decision-theoretic and game-theoretic problems where CDT and EDT perform poorly. Using one simple and coherent decision rule, functional decision theorists (for example) achieve more utility than CDT on Newcomb's problem, more utility than EDT on the smoking lesion problem, and more utility than both in Parfit's hitchhiker problem. In this paper, we define FDT, explore its prescriptions in a number of different decision problems, compare it to CDT and EDT, and give philosophical justifications for FDT as a normative theory of decision-making.

Subfields: Artificial Intelligence, General Decision Sciences, Philosophy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In General Decision Sciences

In Philosophy

Citations in the corpus

AGI Safety Literature Review (2018, background): “tuations. Functional decision theory consolidates years of research about decision theory for embedded agents, and appears to avoid all known weaknesses of both causal and evidential decision theory (Yudkowsky and Soares, 2017). 5.3 Corrigibility By default, agents may resist shutdown and modication”