Combined Reinforcement Learning via Abstract Representations

    national conference on artificial intelligence, 2019.

    Cited by: 16|Bibtex|Views211|Links
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    Abstract:

    In the quest for efficient and robust reinforcement learning methods, both model-free and model-based approaches offer advantages. In this paper we propose a new way of explicitly bridging both approaches via a shared low-dimensional learned encoding of the environment, meant to capture summarizing abstractions. We show that the modularit...More

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