Deep Variational Reinforcement Learning for POMDPs

ICML 2018 Maximilian IglLuisa ZintgrafTuan Anh LeFrank WoodShimon Whiteson

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... (read more)

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