Suppressing modulation instability with reinforcement learning

N.I. Kalmykov, R. Zagidullin, O.Y. Rogov, S. Rykovanov and D.V. Dylov

Chaos, Solitons & Fractals, 2024, vol. 186, issue C

Abstract: Modulation instability is a phenomenon of spontaneous pattern formation in nonlinear media, oftentimes leading to an unpredictable behavior and a degradation of a signal of interest. We propose an approach based on reinforcement learning to suppress the unstable modes in the system by optimizing the parameters for the time modulation of the potential in the nonlinear system. We test our approach in 1D and 2D cases and propose a new class of physically-meaningful reward functions to guarantee tamed instability.

Keywords: Modulation instability; Reinforcement learning; q-learning; Complex Ginzburg–Landau equation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:186:y:2024:i:c:s0960077924007495

DOI: 10.1016/j.chaos.2024.115197

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