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Found 3 papers, 2 papers with code
Meta-Learning the Inductive Biases of Simple Neural Circuits
Training data is always finite, making it unclear how to generalise to unseen situations.
Actionable Neural Representations: Grid Cells from Minimal Constraints
We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings.
A differential Hebbian framework for biologically-plausible motor control
We next show that in a more general case, neural reinforcement learning can be coupled with a feedback controller to reduce errors that arise non-monotonically from the control signal.
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