Connectionist architectures empirically demonstrate cognitive competence through distributed activation patterns that resist decomposition into discrete structured symbols (Rumelhart & McClelland, 1986).

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Cognitive competence(as used in psychology and philosophy of mind): The ability to perform mental tasks like thinking, remembering, understanding language, and solving problems.
Connectionist architectures(as used in cognitive science and AI): Computer systems modeled after how brains work, where many simple processing units connect and communicate with each other rather than following a step-by-step program.
Discrete structured symbols(as used in logic and cognitive science): Individual, clearly distinct units of information—like words or mathematical symbols that have fixed meanings and can be rearranged according to rules.
Distributed activation patterns(as used in neuroscience and artificial intelligence): Information spread across many connected units working together, rather than stored in one specific place—like how a memory might involve multiple brain cells firing at once.

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