论文标题
进化环境中的功能决策理论
Functional Decision Theory in an Evolutionary Environment
论文作者
论文摘要
功能决策理论（FDT）是一种相当新的决策理论方式，也是关于代理如何最大化预期效用的规范观点。决策理论和计算机科学的当前标准是因果决策理论（CDT），在很大程度上被视为优于主要的替代证据决策理论（EDT）。这些理论规定了最大化实用程序的三种不同方法。我们探讨了FDT与CDT和EDT的不同，以及它对FDT代理和人类的行为有什么影响。在先前的研究中已经显示了FDT如何胜过CDT和EDT。我们还表明，FDT在更古典的游戏理论问题上表现良好，并主张将其扩展到人类问题，以表明其优势的潜力是强大的。我们还通过在进化环境中展示它，使FDT更具体，直接与其他理论竞争。
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.
