Paradoxical replay can protect contextual task representations from destructive interference when experience is unbalanced
Hung-Tu Chen,
Matthijs A. A. van der Meer
Abstract:Experience replay is a powerful mechanism to learn efficiently from limited experience. Despite several decades of compelling experimental results, the factors that determine which experiences are selected for replay remain unclear. A particular challenge for current theories is that on tasks that feature unbalanced experience, rats paradoxically replay the less-experienced trajectory. To understand why, we simulated a feedforward neural network with two regimes: rich learning (structured representations tailo… Show more
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