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Meta-Learning through Hebbian Plasticity in Random Networks
[article]
2022
arXiv
pre-print
Lifelong learning and adaptability are two defining aspects of biological agents. Modern reinforcement learning (RL) approaches have shown significant progress in solving complex tasks, however once training is concluded, the found solutions are typically static and incapable of adapting to new information or perturbations. While it is still not completely understood how biological brains learn and adapt so efficiently from experience, it is believed that synaptic plasticity plays a prominent
arXiv:2007.02686v5
fatcat:6bwktudlu5acllvixw52q3ztju