Reinforcement learning, efficient coding, and the statistics of natural tasks

By Matthew Botvinick, Ari Weinstein, Alec Solway, Andrew Barto. 2015

53 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. David Pfau
2. Danilo Jimenez Rezende

Citations in the corpus

• Towards a Definition of Disentangled Representations (2018, background): “A long standing idea in ML is that such shortcomings can be reduced by introducing certain inductive biases into the model architecture that reflect the structure of the underlying data [12, 33, 21, 43].”
• Reinforcement Learning, Fast and Slow. (2019, unknown): “Such work, when viewed through the lens of psychology, neuroscience, and evolutionary and developmental studies, yields a picture in which learning is operating at many time-scales at once—literally running from millennia to milliseconds—with slower time-scales yielding biases that enable faster lea”