Rational theories of diagnostic reasoning assume that the reasoner’s goal is to infer the conditional probability of a cause given an effect from the available data. Typically, diagnostic reasoning is modeled within a statistical inference framework, …
In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the …
This chapter discusses diagnostic reasoning from the perspective of causal inference. The computational framework that provides the foundation for the analyses--probabilistic inference over graphical causal structures--can be used to implement …
Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences …
In sequential diagnostic reasoning, the goal is to infer the probability of a cause event from sequentially observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of …
Whereas the traditional normative benchmark for diagnostic reasoning from effects to causes is provided by purely statistical norms, we here approach the task from the perspective of rational causal inference. The core feature of the presented model …