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February 07, 2020
I'm very interested in AI methods that improve learning efficiency. I found this new paper from DeepMind interesting and thought you might too.
Humans explicitly learn notions of objects, relations, geometry and cardinality in a task-agnostic manner and re-purpose this knowledge to future tasks
First hypothesis: task-agnostic learning of object keypoints can enable fast learning of goal-directed policies.
Second hypothesis: learned keypoints can enable significantly better task-independent exploration.
Search efficiency improvement:
A random action agent would need to search in the space of 18^100 raw actions. However, observing 5 keypoints and T = 20 only has (5×4)^100/20, giving a search space reduction of 10^100