Abstract
Remarkable progress in the mathematics and computer science of probability
has led to a revolution in the scope of probabilistic models. In
particular, `sophisticated' probabilistic methods apply to structured
relational systems such as graphs and grammars, of immediate relevance
to the cognitive sciences. This Special Issue outlines progress in
this rapidly developing field, which provides a potentially unifying
perspective across a wide range of domains and levels of explanation.
Here, we introduce the historical and conceptual foundations of the
approach, explore how the approach relates to studies of explicit
probabilistic reasoning, and give a brief overview of the field as
it stands today.
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