Open access
2026
An Efficient Fully Hardware DQN Accelerator With Parallel Q and Target Networks for Low-Latency Edge AI Application
Experimental results demonstrate that the proposed design preserves learning convergence while reducing training latency, making it well suited for low-power edge DRL applications for autonomous agents.
A. Sumarudin, Andi M. Riyadhus Ilmy, Nana Sutisna et al.
· IEEE Access · 0 citations