connectionist models
Connectionist models refer to computational models of cognition that are based on networks of interconnected nodes or units. These models aim to simulate or mimic human brain processes, where the nodes represent neurons and the connections between them represent synapses. By using these interconnected networks, connectionist models can capture complex cognitive phenomena, such as learning, memory, and decision-making.
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