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Concept learning in a probabilistic language-of-thought. How is it possible and what does it presuppose?
1Tilburg Center for Logic and Philosophy of Science (TiLPS), Tilburg University, Tilburg, The Netherlands m.colombo@uvt.nl; https://mteocolphi.wordpress.com/.
Abstract:
Where does a probabilistic language-of-thought (PLoT) come from? How can we learn new concepts based on probabilistic inferences operating on a PLoT? Here, I explore these questions, sketching a traditional circularity objection to LoT and canvassing various approaches to addressing it. I conclude that PLoT-based cognitive architectures can support genuine concept learning; but, currently, it is unclear that they enjoy more explanatory breadth in relation to concept learning than alternative architectures that do not posit any LoT.
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