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We present BRIEE (Block-structured Representation learning with Interleaved Explore Exploit), an algorithm for efficient reinforcement learning in Markov Decision Processes with block-structured dynamics (i.e., Block MDPs), where rich observations are generated from a set of unknown latent states.
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Chi Jin, Zhuoran Yang, Zhaoran Wang, and Michael I Jordan · 2020
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Michael Laskin, Aravind Srinivas, and Pieter Abbeel · 2020
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Marlos C Machado, Marc G Bellemare, and Michael Bowling · 2020
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Planning to explore via self-supervised world models
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Learning robust state abstractions for hidden-parameter block mdps
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Agnostic reinforcement learning with low-rank mdps and rich observations
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Jiaqi Yang, Wei Hu, Jason D Lee, and Simon S Du · 2022
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