Dynamic-Depth Context Tree Weighting

NeurIPS 2017 Joao V. MessiasShimon Whiteson

Reinforcement learning (RL) in partially observable settings is challenging because the agent’s observations are not Markov. Recently proposed methods can learn variable-order Markov models of the underlying process but have steep memory requirements and are sensitive to aliasing between observation histories due to sensor noise... (read more)

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