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Al Pontryagin or how artificial neural networks learn to control dynamical systems
Computer ScienceNATURE COMMUNICATIONS

Al Pontryagin or how artificial neural networks learn to control dynamical systems

L. Böttcher, N. Antulov-fantulin, et al.

Discover Al Pontryagin, a pioneering neural ordinary differential equation framework developed by Lucas Böttcher, Nino Antulov-Fantulin, and Thomas Asikis. This innovative approach effectively learns control signals for steering complex dynamical systems towards desired states, showcasing remarkable potential in solving tough optimization challenges.... show more
Introduction
Literature Review
Methodology
Key Findings
Discussion
Conclusion
Limitations
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