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Emergence and reconfiguration of modular structure for synaptic neural networks during continual familiarity detection
While advances in artificial intelligence and neuroscience have enabled the emergence of neural networks capable of learning a wide variety of tasks, our understanding of the temporal dynamics of these networks remains limited.
Improving Experience Replay with Successor Representation
This usefulness is quantified as the expected gain from replaying the experience, a quantity often approximated as the prediction error (TD-error).
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