Neuromorphic cognitive architectures are computational frameworks designed to mimic the structure and functioning of the human brain in order to perform tasks such as decision making and action selection. These architectures combine principles of neuroscience with engineering to create systems that can learn, adapt, and make decisions in real-time, similar to biological organisms. They leverage parallel processing, spiking neural networks, and other techniques to achieve efficient and robust cognitive functions.
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