The Nonlinear Library LW - Paper: "FDT in an evolutionary environment" by the gears to ascension
Nov 27, 2023
01:37
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Paper: "FDT in an evolutionary environment", published by the gears to ascension on November 27, 2023 on LessWrong.
I'm not sure what to think of this paper, it's quite long and I haven't finished checking it for sanity. nevertheless, I noticed it hadn't made its way here, and there are mighty few papers that cite the FDT paper, so I figured I'd drop it off rather than leave it sitting open in a tab forever.
Abstract:
Functional decision theory (FDT) is a fairly new mode of decision theory and a normative viewpoint on how an agent should maximize expected utility. The current standard in decision theory and computer science is causal decision theory (CDT), largely seen as superior to the main alternative evidential decision theory (EDT). These theories prescribe three distinct methods for maximizing utility.
We explore how FDT differs from CDT and EDT, and what implications it has on the behavior of FDT agents and humans. It has been shown in previous research how FDT can outperform CDT and EDT. We additionally show FDT performing well on more classical game theory problems and argue for its extension to human problems to show that its potential for superiority is robust. We also make FDT more concrete by displaying it in an evolutionary environment, competing directly against other theories. All relevant code can be found here: https://github.com/noahtopper/FDT-in-an-Evolutionary-Environment.
Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org
I'm not sure what to think of this paper, it's quite long and I haven't finished checking it for sanity. nevertheless, I noticed it hadn't made its way here, and there are mighty few papers that cite the FDT paper, so I figured I'd drop it off rather than leave it sitting open in a tab forever.
Abstract:
Functional decision theory (FDT) is a fairly new mode of decision theory and a normative viewpoint on how an agent should maximize expected utility. The current standard in decision theory and computer science is causal decision theory (CDT), largely seen as superior to the main alternative evidential decision theory (EDT). These theories prescribe three distinct methods for maximizing utility.
We explore how FDT differs from CDT and EDT, and what implications it has on the behavior of FDT agents and humans. It has been shown in previous research how FDT can outperform CDT and EDT. We additionally show FDT performing well on more classical game theory problems and argue for its extension to human problems to show that its potential for superiority is robust. We also make FDT more concrete by displaying it in an evolutionary environment, competing directly against other theories. All relevant code can be found here: https://github.com/noahtopper/FDT-in-an-Evolutionary-Environment.
Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org