Related references
Note: Only part of the references are listed.Reinforcement learning approach for optimal control of multiple electric locomotives in a heavy-haul freight train:A Double-Switch-Q-network architecture
Huiyue Tang et al.
KNOWLEDGE-BASED SYSTEMS (2020)
Adaptive early classification of temporal sequences using deep reinforcement learning
Coralie Martinez et al.
KNOWLEDGE-BASED SYSTEMS (2020)
The autonomous navigation and obstacle avoidance for USVs with ANOA deep reinforcement learning method
Xing Wu et al.
KNOWLEDGE-BASED SYSTEMS (2020)
Generating attentive goals for prioritized hindsight reinforcement learning
Peng Liu et al.
KNOWLEDGE-BASED SYSTEMS (2020)
State representation modeling for deep reinforcement learning based recommendation
Feng Liu et al.
KNOWLEDGE-BASED SYSTEMS (2020)
Spatio-temporal feature fusion for dynamic taxi route recommendation via deep reinforcement learning
Shenggong Ji et al.
KNOWLEDGE-BASED SYSTEMS (2020)
A novel multi-step Q-learning method to improve data efficiency for deep reinforcement learning
Yinlong Yuan et al.
KNOWLEDGE-BASED SYSTEMS (2019)
Application of a Deep Deterministic Policy Gradient Algorithm for Energy-Aimed Timetable Rescheduling Problem
Guang Yang et al.
ENERGIES (2019)
Deep Deterministic Policy Gradient (DDPG)-Based Energy Harvesting Wireless Communications
Chengrun Qiu et al.
IEEE INTERNET OF THINGS JOURNAL (2019)
Human-level control through deep reinforcement learning
Volodymyr Mnih et al.
NATURE (2015)
Share Paper
