Improving performance in SNN-based deep reinforcement learning via transition-aware embeddings
Deep Reinforcement Learning (DRL), which integrates reinforcement learning with deep neural networks (DNNs), has been extensively researched across diverse domains. Robotics, in particular, has seen significant advancements, as DRL enables agents to extract meaningful features from high-dimensional observations and mak...
Hiroto Takigasaki, Takahiro Iwata, S. Yoshioka et al.
· Frontiers in Neurorobotics · 0 citations