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ORCIDNeural Networks, Volume 107
Volume 107, November 2018
- Ron Sun, David Silver, Gerald Tesauro, Guang-Bin Huang
:
Introduction to the special issue on deep reinforcement learning: An editorial. 1-2 - Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning. 3-11 - Mahbubul Alam, Lasitha Vidyaratne, Khan M. Iftekharuddin:
Novel deep generative simultaneous recurrent model for efficient representation learning. 12-22 - Ahmed Hussain Qureshi, Yutaka Nakamura, Yuichiro Yoshikawa, Hiroshi Ishiguro:
Intrinsically motivated reinforcement learning for human-robot interaction in the real-world. 23-33 - Olatunji Mumini Omisore, Shipeng Han, Lingxue Ren, Ahmed Elazab, Hui Li, Talaat Abdelhamid, Nureni Ayofe Azeez, Lei Wang:
Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots. 34-47 - Henghui Zhu, Ioannis Ch. Paschalidis, Michael E. Hasselmo:
Neural circuits for learning context-dependent associations of stimuli. 48-60 - Junfei Qiao, Gongming Wang, Wenjing Li, Min Chen:
An adaptive deep Q-learning strategy for handwritten digit recognition. 61-71
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