Reinforcement learning for hardware acceleration and system-level optimization on FPGA and integrated-circuit platforms: A survey

Reinforcement learning (RL) enables adaptive and autonomous decision-making in embedded, edge, and heterogeneous computing systems. Field-programmable gate arrays (FPGAs) and integrated circuits (ICs) offer low latency, energy efficiency, and architectural flexibility for RL deployment, while introd