Mental State Ascription Using Dynamic Logic
Michal P. Sindlar, Mehdi M. Dastani, Meyer John-Jules · Frontiers in artificial intelligence and applications · 2010
In situations where the behavior of a system must be interpreted because its state is not accessible, it is useful to explain observed behavior in mentalistic terms. This paper presents a formalism based on propositional dynamic logic to model ascription of beliefs, goals, or plans on grounds of observed actions. The formalism is used to provide semantics for an existing approach to abducing the mental state of an observed agent; in doing so it is shown how behavior-producing rules can be given different explanatory interpretations.