Abstract
We argue for the advantages of the probabilistic language of thought (pLOT), a recently emerging approach to modeling human cognition. Work using this framework demonstrates how the pLOT (a) refines the debate between symbols and statistics in cognitive modeling, (b) permits theories that draw on insights from both nativist and empiricist approaches, (c) explains the origins of novel and complex computational concepts, and (d) provides a framework for abstraction that can link sensation and conception. In each of these areas, the pLOT provides a productive middle ground between historical divides in cognitive psychology, pointing to a promising way forward for the field.
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