Abstract

Recently, Yudkowsky and Soares (2018) and Levinstein and Soares (2020) have developed a novel decision theory, Functional Decision Theory (FDT). They claim FDT outperforms both Evidential Decision Theory (EDT) and Causal Decision Theory (CDT). Yet FDT faces several challenges. First, it yields some very counterintuitive results (Schwarz 2018; MacAskill 2019). Second, it requires a theory of counterpossibles, for which even Yudkowsky and Soares (2018) and Levinstein and Soares (2020) admit we lack a “full” or “satisfactory” account. Here, I focus on the latter problem of counterpossibles. My aim is to establish two claims. First, the problem of counterpossibles does not even arise without a fairly strong assumptionone that rarely applies to human agents, but may apply to artificial agents. And second, even given this assumption, the problem is solvable, though how best to solve it remains an open question.