Deep Exploration via Bootstrapped DQN. 02/15/2016 ∙ by Ian Osband, et al. ∙ Google ∙ Stanford University ∙ 0 ∙ share Efficient exploration in complex environments remains a major challenge for reinforcement learning. We propose bootstrapped DQN, a simple algorithm that explores in a computationally and statistically efficient manner through use of randomized value functions. Unlike.
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