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Towards continual task learning in artificial neural networks: current approaches and insights from neuroscience
[article]
2021
arXiv
pre-print
The innate capacity of humans and other animals to learn a diverse, and often interfering, range of knowledge and skills throughout their lifespan is a hallmark of natural intelligence, with obvious evolutionary motivations. In parallel, the ability of artificial neural networks (ANNs) to learn across a range of tasks and domains, combining and re-using learned representations where required, is a clear goal of artificial intelligence. This capacity, widely described as continual learning, has
arXiv:2112.14146v1
fatcat:xu3a3blkxrhkvmutosnwrlalum