Iterative Model-Based Reinforcement Learning Using Simulations in the Differentiable Neural Computer

17 Jun 2019Adeel MuftiSvetlin PenkovSubramanian Ramamoorthy

We propose a lifelong learning architecture, the Neural Computer Agent (NCA), where a Reinforcement Learning agent is paired with a predictive model of the environment learned by a Differentiable Neural Computer (DNC). The agent and DNC model are trained in conjunction iteratively... (read more)

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