论文标题
使用增强剂学习剂绘制电感器布局：VCO电感器的方法和应用
Drawing Inductor Layout with a Reinforcement Learning Agent: Method and Application for VCO Inductors
论文作者
论文摘要
电压控制的振荡器（VCO）电感器的设计是一项费力且耗时的任务，通常是由人类专家手动完成的。在本文中，我们提出了一个使用增强学习（RL）自动化VCO电感器设计的框架。我们将问题提出为顺序过程，其中一个接一个地绘制了电线段，直到创建完整的电感器。然后，我们采用RL代理来学习绘制符合某些目标规格的电感器。鉴于需要在整个电路设计周期中调整目标规范，我们还开发了一种变体，在该变体中，代理可以学会快速适应以绘制适度不同目标规范的新电感器。我们的经验结果表明，所提出的框架在自动生成满足或超过目标规范的VCO电感器方面取得了成功。
Design of Voltage-Controlled Oscillator (VCO) inductors is a laborious and time-consuming task that is conventionally done manually by human experts. In this paper, we propose a framework for automating the design of VCO inductors, using Reinforcement Learning (RL). We formulate the problem as a sequential procedure, where wire segments are drawn one after another, until a complete inductor is created. We then employ an RL agent to learn to draw inductors that meet certain target specifications. In light of the need to tweak the target specifications throughout the circuit design cycle, we also develop a variant in which the agent can learn to quickly adapt to draw new inductors for moderately different target specifications. Our empirical results show that the proposed framework is successful at automatically generating VCO inductors that meet or exceed the target specification.
