Deep Reinforcement Learning and Adaptive Dynamic Programming

Posted on December 24, 2016 in Special Issue
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Deep Reinforcement Learning and Adaptive Dynamic Programming

Thu 30 Mar 2017

• New algorithms of deep RL or ADP;
• Theory of deep RL or ADP;
• Deep RL or ADP with transfer learning;
• Deep RL or ADP with advanced search algorithms;
• Multi-agent RL or ADP;
• Hierarchical RL or ADP;
• Event-driven RL or ADP;
• Theoretical foundation of RL or ADP in convergence, stability, robustness, and etc. ;
• Data-driven learning and control;
• Control with advanced machine learning;
• Optimal decision and control of cyber-physical systems;
• Autonomous decision and control using neural structures;
• Brain-like control design and applications;
• New neural network topologies from neurocognitive psychology studies;
• Neurocomputing structures for fast decision and control in dynamic environments;
• Applications in realistic and complicated systems