Learning Quantized Continuous Controllers for Integer Hardware 事件

Learning Quantized Continuous Controllers for Integer Hardware arXiv:2511.07046v4 Announce Type: replace-cross Abstract: Deploying continuous-control reinforcement learning policies on embedded hardware requires meeting tight latency and power budgets. Small FPGAs can deliver these, but only if costly floating-point pipelines are avoided. We study quantization-aware training (QAT) of policies for integer inference and we present a learning-to-hardware pipeline that automatically selects low-bit