Identifying subtree perfectness in decision trees
Nathan Huntley, Matthias C. M. Troffaes

TL;DR
This paper introduces the concept of subtree perfectness in decision trees, providing a simple criterion to determine when choice functions satisfy this property, which is crucial for consistent and efficient decision analysis.
Contribution
It offers a non-technical criterion for subtree perfectness, analyzing various choice functions and their compatibility with this property, extending understanding beyond expected utility maximization.
Findings
Almost no choice function satisfies subtree perfectness in general.
Expected utility maximization always satisfies subtree perfectness.
Certain choice functions can satisfy subtree perfectness under specific structural restrictions.
Abstract
In decision problems, often, utilities and probabilities are hard to determine. In such cases, one can resort to so-called choice functions. They provide a means to determine which options in a particular set are optimal, and allow incomparability among any number of options. Applying choice functions in sequential decision problems can be highly non-trivial, as the usual properties of maximising expected utility may no longer be satisfied. In this paper, we study one of these properties: we revisit and reinterpret Selten's concept of subgame perfectness in the context of decision trees, leading us to the concept of subtree perfectness, which basically says that the optimal solution of a decision tree should not depend on any larger tree it may be embedded in. In other words, subtree perfectness excludes counterfactual reasoning, and therefore may be desirable from some philosophical…
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Taxonomy
TopicsBayesian Modeling and Causal Inference · Decision-Making and Behavioral Economics · Explainable Artificial Intelligence (XAI)
