AlphaGo-driven generative machine learning framework for inverse topology synthesis and optimization of planar antennas.

Xiaobo Wang¹, Suomin Cui², Moein Nazari², Gang Kang², Jian Liu²

¹Cadence Design Systems (United States), San Jose, USA. xbwang@cadence.com.

²Cadence Design Systems (United States), San Jose, USA.

Abstract

This paper proposes an AlphaGo-inspired algorithm for automated antenna generation. Analogous to how AlphaGo navigates the discrete move-space of a board game, our framework treats antenna design as a sequential decision-making process. With an innovated topology generation rule, a Monte Carlo tree search-based optimization is applied to guide the moving steps to approach good designs. During the…

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