45 citations · 220 across the 21 of their papers we have counts for
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cs.AI2018
Fast Exploration with Simplified Models and Approximately Optimistic Planning in Model Based Reinforcement Learning
Ramtin Keramati, Jay Whang, Patrick Cho +1
Humans learn to play video games significantly faster than the state-of-the-art reinforcement learning (RL) algorithms. People seem to build simple models that are easy to learn to…
cs.AI2018
Efficient Exploration through Bayesian Deep Q-Networks
Kamyar Azizzadenesheli, Animashree Anandkumar
We study reinforcement learning (RL) in high dimensional episodic Markov decision processes (MDP). We consider value-based RL when the optimal Q-value is a linear function of d-dim…