Deep variational reinforcement learning for POMDPs

Deep variational reinforcement learning for POMDPs

Many real-world sequential decision making problems are partially observable by nature, and the environment model is typically unknown. Consequently, there is great need for reinforcement learning methods that can tackle such problems given only a stream of incomplete and noisy observations. In this...

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Bibliografische gegevens
Hoofdauteurs: Igl, M, Zintgraf, L, Le, T, Wood, F, Whiteson, S
Formaat: Conference item
Gepubliceerd in: Journal of Machine Learning Research 2018

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