Operators have many mental models of a single system which represent different levels of an abstraction hierarchy, different levels of part-whole decomposition, and different types of causality. Operators change the levels or types of cognition from moment to moment within a problem. This hierarchy has been suggested as a model of cognition, but has not been implemented. Artificial cognition should mimic the errors made by humans as well as providing successful reasoning. The form of errors reflect the skill, rule, knowledge typology.
Operators try to avoid reasoning and use rules whenever possible.
Reasoning is rare in the wild. There are a number of characteristics of diagnostic reasoning which are considered characteristic of operators, but which are sometimes thought of as errors, and sometimes as strategies. For example, operators fixate rapidly on a single hypothesis, and seek evidence to support it, rather than testing hypotheses. Mental models are often unstable and do not support hypothesis testing well unless they have become rule or skill-based. Identical information may have different meaning depending on context.