distinguishes dogs from non-dogs, and hence to correctly categorize them. This kind of learning, called reinforcement learning in the behavioral literature and supervised learning in the computational literature, is fundamentally dependent on the possibility of error, and error-correction. Miscategorization—examples of nonmembers of the category—must always exist, not only to make the category learnable, but for the category to exist and be definable at all. See also Categorical perception Classification (general theory) Library classification Multi-label classification Pattern recognition Statistical classification Symbol grounding problem Characterization (mathematics) Knolling References External links To Cognize is to Categorize: Cognition is Categorization Wikipedia Categories Visualizer Interdisciplinary Introduction to Categorization: Interview with Dvora Yanov (political sciences), Amie Thomasson (philosophy) and Thomas Serre (artificial intelligence) Cognition Concepts in epistemology Knowledge representation Semantics