Gait switching and targeted navigation of microswimmers via deep reinforcement learning

Abstract

Biomedical applications of artificial microswimmers rely on efficient navigation strategies within complex and unpredictable fluid environments. Here, the authors use artificial intelligence to model and design microswimmers that are capable of self-learning efficient navigation strategies by adaptively switching between different locomotory gaits.