Recently in deep learning, there's been a surge in learning how to use memories as part of the optimisation process (i.e. LSTM's and Stacks). However, these aren't really analogous to how a cognitive systems learns how to use it's working memory.

Are there models of how working memory can be learned to be optimally leveraged? Maybe via reinforcement learning?