822 citations · 2.4k across the 23 of their papers we have counts for
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cs.LG2016★ 822 cited
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Tejas D. Kulkarni, Karthik R. Narasimhan, Ardavan Saeedi +1
Learning goal-directed behavior in environments with sparse feedback is a major challenge for reinforcement learning algorithms. The primary difficulty arises due to insufficient e…
cs.LG2016★ 33 cited
Understanding Visual Concepts with Continuation Learning
William F. Whitney, Michael Chang, Tejas Kulkarni +1
We introduce a neural network architecture and a learning algorithm to produce factorized symbolic representations. We propose to learn these concepts by observing consecutive fram…