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.

本研究介绍了一种自动化设计VCO电感的框架，使用强化学习作为方法。在该框架中，我们将问题制定为顺序过程，并使用强化学习代理学习画出特定规格的电感。该框架会连续画出导线段，直到生成完整的电感并满足要求。针对需要在电路设计周期内调整目标规格的需求，我们还开发了一种变体，学习可以快速适应新目标规格的电感。实验结果表明，该框架能够成功生成满足或超出目标规格的VCO电感。

使用强化学习代理绘制电感布局: VCO电感器方法和应用