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  1. Making Sense of Sensory Input.Richard Evans, José Hernández-Orallo, Johannes Welbl, Pushmeet Kohli & Marek Sergot - 2021 - Artificial Intelligence 293 (C):103438.
    This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is a (...)
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