Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks

29 Jan 2019Dongqi HanKenji DoyaJun Tani

Recurrent neural networks (RNNs) for reinforcement learning (RL) have shown distinct advantages, e.g., solving memory-dependent tasks and meta-learning. However, little effort has been spent on improving RNN architectures and on understanding the underlying neural mechanisms for performance gain... (read more)

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