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

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

29 January 2019

Dongqi Han

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

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Title
Compositional Learning of Visually-Grounded Concepts Using Reinforcement Zijun Lin Haidi Azaman M Ganesh Kumar Cheston Tan CoGe OffRL 176 3 0 08 Sep 2023
Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning Giseung Park Sungho Choi Y. Sung OffRL 121 3 0 10 Dec 2021
Goal-Directed Planning by Reinforcement Learning and Active Inference Dongqi Han Kenji Doya Jun Tani 81 2 0 18 Jun 2021
One-shot learning of paired association navigation with biologically plausible schemas M Ganesh Kumar Cheston Tan C. Libedinsky S. Yen A. Tan 137 3 0 07 Jun 2021
A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental RobotsNeural Networks (NN), 2021 T. Taniguchi Hiroshi Yamakawa Takayuki Nagai Kenji Doya M. Sakagami Masahiro Suzuki Tomoaki Nakamura Akira Taniguchi 168 28 0 15 Mar 2021
Hierarchical principles of embodied reinforcement learning: A review Manfred Eppe Christian Gumbsch Matthias Kerzel Phuong D. H. Nguyen Martin Volker Butz S. Wermter 225 11 0 18 Dec 2020
Explainability in Deep Reinforcement Learning Alexandre Heuillet Fabien Couthouis Natalia Díaz Rodríguez XAI 574 306 0 15 Aug 2020
Variational Recurrent Models for Solving Partially Observable Control TasksInternational Conference on Learning Representations (ICLR), 2019 Dongqi Han Kenji Doya Jun Tani DRL OffRL 103 70 0 23 Dec 2019