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Modular Continual Learning in a Unified Visual Environment
A core aspect of human intelligence is the ability to learn new tasks quickly and switch between them flexibly.
A Useful Motif for Flexible Task Learning in an Embodied Two-Dimensional Visual Environment
Recent results from neuroscience and artificial intelligence suggest the role of the general purpose visual representation may be played by a deep convolutional neural network, and give some clues how task modules based on such a representation might be discovered and constructed.
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