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Reuse of Neural Modules for General Video Game Playing
[article]
2015
arXiv
pre-print
A general approach to knowledge transfer is introduced in which an agent controlled by a neural network adapts how it reuses existing networks as it learns in a new domain. Networks trained for a new domain can improve their performance by routing activation selectively through previously learned neural structure, regardless of how or for what it was learned. A neuroevolution implementation of this approach is presented with application to high-dimensional sequential decision-making domains.
arXiv:1512.01537v1
fatcat:t6i5qmlpcfcv3frh3np4xa6d44