Combining brain-computer interfaces with deep reinforcement learning for robot training: a feasibility study in a simulation environment
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Deep reinforcement learning (RL) is used as a strategy to teach robot agents how to autonomously learn complex tasks. While sparsity is a natural way to define a reward in realistic robot scenarios, it provides poor learning signals for the agent, thus making ... ...
