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Learning at variable attentional load requires cooperation between working memory, meta-learning and attention-augmented reinforcement learning
[article]
2020
bioRxiv
pre-print
Flexible learning of changing reward contingencies can be realized with different strategies. A fast learning strategy involves forming a working memory of rewarding experiences with objects to improve future choices. A slower learning strategy uses prediction errors to gradually update value expectations to improve choices. How the fast and slow strategies work together in scenarios with real-world stimulus complexity is not well known. Here, we disentangle their relative contributions in
doi:10.1101/2020.09.27.315432
fatcat:cigb5t42kzandkjxefnqlykesq