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Paper-Title: Reinforcement Learning, Fast and Slow
#Deepmind #Cognitive_Science
Link to the paper: https://www.cell.com/action/showPdf?pii=S1364-6613%2819%2930061-0

TL;DR: [1] This paper reviews recent techniques in deep RL that narrow the gap in learning speed between humans and agents, & demonstrate an interplay between fast and slow learning w/ parallels in animal/human cognition.
[2] When episodic memory is used in reinforcement learning, an explicit record of past events is maintained for making decisions about the current situation. The action chosen is the one associated with the highest value, based on the outcomes of similar past situations.
[3] Meta-reinforcement learning quickly adapts to new tasks by learning strong inductive biases. This is done via a slower outer learning loop training on the distribution of tasks, leading to an inner loop that rapidly adapts by maintaining a history of past actions and observations.
Free «Advanced Deep Learning and Reinforcement Learning» course.

#DeepMind researchers have released video recordings of lectures from «Advanced Deep Learning and Reinforcement Learning» a course on deep RL taught at #UCL earlier this year.

YouTube Playlist: https://www.youtube.com/playlist?list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs

#course #video #RL #DL