Shaping Belief States with Generative Environment Models for RL

Frederic Besse
Frederic Besse
Hamza Merzic
Hamza Merzic
Aäron van den Oord
Aäron van den Oord

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), pp. 13475-13487, 2019.

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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org
Keywords:
reinforcement learning

Abstract:

When agents interact with a complex environment, they must form and maintain beliefs about the relevant aspects of that environment. We propose a way to efficiently train expressive generative models in complex environments. We show that a predictive algorithm with an expressive generative model can form stable belief-states in visually r...More

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